def test_div_ff_2 (self):
src1_data = ( 5, 9, -15, 1024)
src2_data = (10, 3, -5, 64)
expected_result = (0.5, 3, 3, 16)
op = gr.divide_ff (2)
self.help_ff ((src1_data, src2_data),
expected_result, op, port_prefix='float_in_')
def __init__(self, options):
self.rx = raw.ofdm_demod(options, (options.nsr is not None) and 4 or 2)
self.params = self.rx.params
symbol_size = self.params.data_tones * gr.sizeof_gr_complex
gr.hier_block2.__init__(self, "RX",
gr.io_signature(1,1, gr.sizeof_gr_complex),
gr.io_signature(1,1, symbol_size))
ff = raw.fix_frame(symbol_size, options.size)
self.connect(self, self.rx, (ff,0), self)
self.connect((self.rx,1), (ff,1))
# noise-to-signal ratio estimate
# TODO: make it a proper output from the block
if options.nsr is not None:
nsr = gr.divide_ff()
self.connect((self.rx,2), gr.integrate_ff(options.size), (nsr,0))
self.connect((self.rx,3), gr.integrate_ff(options.size), (nsr,1))
self.connect(nsr, gr.file_sink(gr.sizeof_float, options.nsr)) # what to do with the output?
acq = self.rx.ofdm_recv.frame_acq
acq.set_min_symbols(options.size)
if options.numpkts is not None:
acq.set_num_frames(options.numpkts)
self.size = options.size
if options.log:
self.connect((self.rx,0), gr.file_sink(symbol_size, 'rx-ofdmdemod.dat'))
self.connect((self.rx,1), gr.file_sink(gr.sizeof_char, 'rx-ofdmdemod.datb'))
self.connect((ff,0), gr.file_sink(symbol_size, 'rx-fixframe.dat'))
def __init__(self, fft_length, pn_weights):
gr.hier_block2.__init__(self, "modified_timing_metric",
gr.io_signature(1,1,gr.sizeof_gr_complex),
gr.io_signature(1,1,gr.sizeof_float))
assert(len(pn_weights) == fft_length)
self.input = gr.kludge_copy(gr.sizeof_gr_complex)
self.connect(self,self.input)
# P(d) = sum(0 to L-1, conj(delayed(r)) * r)
conj = gr.conjugate_cc()
mixer = gr.multiply_cc()
nominator = gr.fir_filter_ccf(1,[pn_weights[fft_length-i-1]*pn_weights[fft_length/2-i-1] for i in range(fft_length/2)])
self.connect(self.input, delay(gr.sizeof_gr_complex,fft_length/2), conj, (mixer,0))
self.connect(self.input, (mixer,1))
self.connect(mixer, nominator)
# moving_avg = P(d)
# R(d)
denominator = schmidl_denominator(fft_length)
# |P(d)| ** 2 / (R(d)) ** 2
p_mag_sqrd = gr.complex_to_mag_squared()
r_sqrd = gr.multiply_ff()
self.timing_metric = gr.divide_ff()
self.connect(nominator, p_mag_sqrd, (self.timing_metric,0))
self.connect(self.input, denominator, (r_sqrd,0))
self.connect(denominator, (r_sqrd,1))
self.connect(r_sqrd, (self.timing_metric,1))
self.connect(self.timing_metric, self)
def test_div_ff_2 (self):
src1_data = ( 5, 9, -15, 1024)
src2_data = (10, 3, -5, 64)
expected_result = (0.5, 3, 3, 16)
op = gr.divide_ff ()
self.help_ff ((src1_data, src2_data),
expected_result, op)
def __init__(self, fft_length):
gr.hier_block2.__init__(self, "timing_metric",
gr.io_signature(1,1,gr.sizeof_gr_complex),
gr.io_signature(1,1,gr.sizeof_float))
self.input = gr.kludge_copy(gr.sizeof_gr_complex)
self.connect(self,self.input)
# P(d)
nominator = schmidl_nominator(fft_length)
# R(d)
denominator = schmidl_denominator(fft_length)
# |P(d)| ** 2 / (R(d)) ** 2
p_mag_sqrd = gr.complex_to_mag_squared()
r_sqrd = gr.multiply_ff()
self.timing_metric = gr.divide_ff()
self.connect(self.input, nominator, p_mag_sqrd, (self.timing_metric,0))
self.connect(self.input, denominator, (r_sqrd,0))
self.connect(denominator, (r_sqrd,1))
self.connect(r_sqrd, (self.timing_metric,1))
self.connect(self.timing_metric, self)
# calculate epsilon from P(d), epsilon is normalized fractional frequency offset
#angle = gr.complex_to_arg()
#self.epsilon = gr.multiply_const_ff(1.0/math.pi)
#self.connect(nominator, angle, self.epsilon)
try:
gr.hier_block.update_var_names(self, "schmidl", vars())
gr.hier_block.update_var_names(self, "schmidl", vars(self))
except:
pass
def test_div_ff_1(self):
src1_data = (1, 2, 4, -8)
expected_result = (1, 0.5, 0.25, -.125)
op = gr.divide_ff(1)
self.help_ff((src1_data, ),
expected_result,
op,
port_prefix='SINGLE_PORT')
def test_div_ff_3 (self):
src1_data = ( 5, 9, -15, 1024)
src2_data = (10, 3, -5, 64)
src3_data = (2, 3, -.5, -4)
expected_result = (0.25, 1, -6, -4)
op = gr.divide_ff (3)
self.help_ff ((src1_data, src2_data, src3_data),
expected_result, op, port_prefix='float_in_')
def test_div_ff_2(self):
src1_data = (5, 9, -15, 1024)
src2_data = (10, 3, -5, 64)
expected_result = (0.5, 3, 3, 16)
op = gr.divide_ff(2)
self.help_ff((src1_data, src2_data),
expected_result,
op,
port_prefix='float_in_')
def test_div_ff_4 (self):
src1_data = ( 5, 9, -15, 1024)
src2_data = (10, 3, -5, 64)
src3_data = (2, 3, -.5, -4)
src4_data = (-0.5, -1 ,-3, 2)
expected_result = (-0.5, -1, 2, -2)
op = gr.divide_ff (4)
self.help_ff ((src1_data, src2_data, src3_data, src4_data),
expected_result, op, port_prefix='float_in_')
def test_div_ff_3(self):
src1_data = (5, 9, -15, 1024)
src2_data = (10, 3, -5, 64)
src3_data = (2, 3, -.5, -4)
expected_result = (0.25, 1, -6, -4)
op = gr.divide_ff(3)
self.help_ff((src1_data, src2_data, src3_data),
expected_result,
op,
port_prefix='float_in_')
def test_div_ff_4(self):
src1_data = (5, 9, -15, 1024)
src2_data = (10, 3, -5, 64)
src3_data = (2, 3, -.5, -4)
src4_data = (-0.5, -1, -3, 2)
expected_result = (-0.5, -1, 2, -2)
op = gr.divide_ff(4)
self.help_ff((src1_data, src2_data, src3_data, src4_data),
expected_result,
op,
port_prefix='float_in_')
def __init__(self, data_tones, num_symbols, mode=0):
symbol_size = data_tones * gr.sizeof_gr_complex
gr.hier_block2.__init__(self, "SNR",
gr.io_signature2(2,2, symbol_size, symbol_size),
gr.io_signature(1,1, gr.sizeof_float))
sub = gr.sub_cc(data_tones)
self.connect((self,0), (sub,0))
self.connect((self,1), (sub,1))
err = gr.complex_to_mag_squared(data_tones);
self.connect(sub, err);
pow = gr.complex_to_mag_squared(data_tones);
self.connect((self,1), pow);
if mode == 0:
# one snr per symbol (num_symbols is ignored)
snr = gr.divide_ff()
self.connect(pow, gr.vector_to_stream(gr.sizeof_float, data_tones),
gr.integrate_ff(data_tones), (snr,0))
self.connect(err, gr.vector_to_stream(gr.sizeof_float, data_tones),
gr.integrate_ff(data_tones), (snr,1))
out = snr
elif mode == 1:
# one snr per packet
snr = gr.divide_ff()
self.connect(pow, gr.vector_to_stream(gr.sizeof_float, data_tones),
gr.integrate_ff(data_tones*num_symbols), (snr,0))
self.connect(err, gr.vector_to_stream(gr.sizeof_float, data_tones),
gr.integrate_ff(data_tones*num_symbols), (snr,1))
out = snr
elif mode == 2:
# one snr per frequency bin
snr = gr.divide_ff(data_tones)
self.connect(pow, raw.symbol_avg(data_tones, num_symbols), (snr,0))
self.connect(err, raw.symbol_avg(data_tones, num_symbols), (snr,1))
out = gr.vector_to_stream(gr.sizeof_float, data_tones)
self.connect(snr, out)
self.connect(out, gr.nlog10_ff(10), self)
def __init__(self, audio_rate):
gr.hier_block2.__init__(
self,
"standard_squelch",
gr.io_signature(1, 1, gr.sizeof_float), # Input signature
gr.io_signature(1, 1, gr.sizeof_float)) # Output signature
self.input_node = gr.add_const_ff(0) # FIXME kludge
self.low_iir = gr.iir_filter_ffd((0.0193, 0, -0.0193),
(1, 1.9524, -0.9615))
self.low_square = gr.multiply_ff()
self.low_smooth = gr.single_pole_iir_filter_ff(
1 / (0.01 * audio_rate)) # 100ms time constant
self.hi_iir = gr.iir_filter_ffd((0.0193, 0, -0.0193),
(1, 1.3597, -0.9615))
self.hi_square = gr.multiply_ff()
self.hi_smooth = gr.single_pole_iir_filter_ff(1 / (0.01 * audio_rate))
self.sub = gr.sub_ff()
self.add = gr.add_ff()
self.gate = gr.threshold_ff(0.3, 0.43, 0)
self.squelch_lpf = gr.single_pole_iir_filter_ff(1 /
(0.01 * audio_rate))
self.div = gr.divide_ff()
self.squelch_mult = gr.multiply_ff()
self.connect(self, self.input_node)
self.connect(self.input_node, (self.squelch_mult, 0))
self.connect(self.input_node, self.low_iir)
self.connect(self.low_iir, (self.low_square, 0))
self.connect(self.low_iir, (self.low_square, 1))
self.connect(self.low_square, self.low_smooth, (self.sub, 0))
self.connect(self.low_smooth, (self.add, 0))
self.connect(self.input_node, self.hi_iir)
self.connect(self.hi_iir, (self.hi_square, 0))
self.connect(self.hi_iir, (self.hi_square, 1))
self.connect(self.hi_square, self.hi_smooth, (self.sub, 1))
self.connect(self.hi_smooth, (self.add, 1))
self.connect(self.sub, (self.div, 0))
self.connect(self.add, (self.div, 1))
self.connect(self.div, self.gate, self.squelch_lpf,
(self.squelch_mult, 1))
self.connect(self.squelch_mult, self)
def __init__(self, vlen):
gr.hier_block2.__init__(
self, "snr_estimator",
gr.io_signature(2, 2, gr.sizeof_gr_complex * vlen),
gr.io_signature(1, 1, gr.sizeof_float))
reference = gr.kludge_copy(gr.sizeof_gr_complex * vlen)
received = gr.kludge_copy(gr.sizeof_gr_complex * vlen)
self.connect((self, 0), reference)
self.connect((self, 1), received)
received_conjugated = gr.conjugate_cc(vlen)
self.connect(received, received_conjugated)
R_innerproduct = gr.multiply_vcc(vlen)
self.connect(reference, R_innerproduct)
self.connect(received_conjugated, (R_innerproduct, 1))
R_sum = vector_sum_vcc(vlen)
self.connect(R_innerproduct, R_sum)
R = gr.complex_to_mag_squared()
self.connect(R_sum, R)
received_magsqrd = gr.complex_to_mag_squared(vlen)
reference_magsqrd = gr.complex_to_mag_squared(vlen)
self.connect(received, received_magsqrd)
self.connect(reference, reference_magsqrd)
received_sum = vector_sum_vff(vlen)
reference_sum = vector_sum_vff(vlen)
self.connect(received_magsqrd, received_sum)
self.connect(reference_magsqrd, reference_sum)
P = gr.multiply_ff()
self.connect(received_sum, (P, 0))
self.connect(reference_sum, (P, 1))
denominator = gr.sub_ff()
self.connect(P, denominator)
self.connect(R, (denominator, 1))
rho_hat = gr.divide_ff()
self.connect(R, rho_hat)
self.connect(denominator, (rho_hat, 1))
self.connect(rho_hat, self)
def __init__(self,vlen):
gr.hier_block2.__init__(self,"snr_estimator",
gr.io_signature(2,2,gr.sizeof_gr_complex*vlen),
gr.io_signature(1,1,gr.sizeof_float))
reference = gr.kludge_copy(gr.sizeof_gr_complex*vlen)
received = gr.kludge_copy(gr.sizeof_gr_complex*vlen)
self.connect((self,0),reference)
self.connect((self,1),received)
received_conjugated = gr.conjugate_cc(vlen)
self.connect(received,received_conjugated)
R_innerproduct = gr.multiply_vcc(vlen)
self.connect(reference,R_innerproduct)
self.connect(received_conjugated,(R_innerproduct,1))
R_sum = vector_sum_vcc(vlen)
self.connect(R_innerproduct,R_sum)
R = gr.complex_to_mag_squared()
self.connect(R_sum,R)
received_magsqrd = gr.complex_to_mag_squared(vlen)
reference_magsqrd = gr.complex_to_mag_squared(vlen)
self.connect(received,received_magsqrd)
self.connect(reference,reference_magsqrd)
received_sum = vector_sum_vff(vlen)
reference_sum = vector_sum_vff(vlen)
self.connect(received_magsqrd,received_sum)
self.connect(reference_magsqrd,reference_sum)
P = gr.multiply_ff()
self.connect(received_sum,(P,0))
self.connect(reference_sum,(P,1))
denominator = gr.sub_ff()
self.connect(P,denominator)
self.connect(R,(denominator,1))
rho_hat = gr.divide_ff()
self.connect(R,rho_hat)
self.connect(denominator,(rho_hat,1))
self.connect(rho_hat,self)
def __init__(self, fg):
self.split = gr.multiply_const_ff(1)
self.sqr = gr.multiply_ff()
self.int0 = gr.iir_filter_ffd([0.004, 0], [0, 0.999])
self.offs = gr.add_const_ff(-30)
self.gain = gr.multiply_const_ff(70)
self.log = gr.nlog10_ff(10, 1)
self.agc = gr.divide_ff()
fg.connect(self.split, (self.agc, 0))
fg.connect(self.split, (self.sqr, 0))
fg.connect(self.split, (self.sqr, 1))
fg.connect(self.sqr, self.int0)
fg.connect(self.int0, self.log)
fg.connect(self.log, self.offs)
fg.connect(self.offs, self.gain)
fg.connect(self.gain, (self.agc, 1))
gr.hier_block.__init__(self, fg, self.split, self.agc)
def __init__(self, fg):
self.split = gr.multiply_const_ff(1)
self.sqr = gr.multiply_ff()
self.int0 = gr.iir_filter_ffd([.004, 0], [0, .999])
self.offs = gr.add_const_ff(-30)
self.gain = gr.multiply_const_ff(70)
self.log = gr.nlog10_ff(10, 1)
self.agc = gr.divide_ff()
fg.connect(self.split, (self.agc, 0))
fg.connect(self.split, (self.sqr, 0))
fg.connect(self.split, (self.sqr, 1))
fg.connect(self.sqr, self.int0)
fg.connect(self.int0, self.log)
fg.connect(self.log, self.offs)
fg.connect(self.offs, self.gain)
fg.connect(self.gain, (self.agc, 1))
gr.hier_block.__init__(self, fg, self.split, self.agc)
def __init__(self, audio_rate):
gr.hier_block2.__init__(self, "standard_squelch",
gr.io_signature(1, 1, gr.sizeof_float), # Input signature
gr.io_signature(1, 1, gr.sizeof_float)) # Output signature
self.input_node = gr.add_const_ff(0) # FIXME kludge
self.low_iir = gr.iir_filter_ffd((0.0193,0,-0.0193),(1,1.9524,-0.9615))
self.low_square = gr.multiply_ff()
self.low_smooth = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate)) # 100ms time constant
self.hi_iir = gr.iir_filter_ffd((0.0193,0,-0.0193),(1,1.3597,-0.9615))
self.hi_square = gr.multiply_ff()
self.hi_smooth = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate))
self.sub = gr.sub_ff();
self.add = gr.add_ff();
self.gate = gr.threshold_ff(0.3,0.43,0)
self.squelch_lpf = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate))
self.div = gr.divide_ff()
self.squelch_mult = gr.multiply_ff()
self.connect (self, self.input_node)
self.connect (self.input_node, (self.squelch_mult, 0))
self.connect (self.input_node,self.low_iir)
self.connect (self.low_iir,(self.low_square,0))
self.connect (self.low_iir,(self.low_square,1))
self.connect (self.low_square,self.low_smooth,(self.sub,0))
self.connect (self.low_smooth, (self.add,0))
self.connect (self.input_node,self.hi_iir)
self.connect (self.hi_iir,(self.hi_square,0))
self.connect (self.hi_iir,(self.hi_square,1))
self.connect (self.hi_square,self.hi_smooth,(self.sub,1))
self.connect (self.hi_smooth, (self.add,1))
self.connect (self.sub, (self.div, 0))
self.connect (self.add, (self.div, 1))
self.connect (self.div, self.gate, self.squelch_lpf, (self.squelch_mult,1))
self.connect (self.squelch_mult, self)
def __init__ ( self, fft_length ):
gr.hier_block2.__init__(self, "recursive_timing_metric",
gr.io_signature(1,1,gr.sizeof_gr_complex),
gr.io_signature(1,1,gr.sizeof_float))
self.input = gr.kludge_copy(gr.sizeof_gr_complex)
self.connect(self, self.input)
# P(d) = sum(0 to L-1, conj(delayed(r)) * r)
conj = gr.conjugate_cc()
mixer = gr.multiply_cc()
mix_delay = delay(gr.sizeof_gr_complex,fft_length/2+1)
mix_diff = gr.sub_cc()
nominator = accumulator_cc()
inpdelay = delay(gr.sizeof_gr_complex,fft_length/2)
self.connect(self.input, inpdelay,
conj, (mixer,0))
self.connect(self.input, (mixer,1))
self.connect(mixer,(mix_diff,0))
self.connect(mixer, mix_delay, (mix_diff,1))
self.connect(mix_diff,nominator)
rmagsqrd = gr.complex_to_mag_squared()
rm_delay = delay(gr.sizeof_float,fft_length+1)
rm_diff = gr.sub_ff()
denom = accumulator_ff()
self.connect(self.input,rmagsqrd,rm_diff,gr.multiply_const_ff(0.5),denom)
self.connect(rmagsqrd,rm_delay,(rm_diff,1))
ps = gr.complex_to_mag_squared()
rs = gr.multiply_ff()
self.connect(nominator,ps)
self.connect(denom,rs)
self.connect(denom,(rs,1))
div = gr.divide_ff()
self.connect(ps,div)
self.connect(rs,(div,1))
self.connect(div,self)
def __init__(self, fft_length):
gr.hier_block2.__init__(self, "recursive_timing_metric",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_float))
self.input = gr.kludge_copy(gr.sizeof_gr_complex)
self.connect(self, self.input)
# P(d) = sum(0 to L-1, conj(delayed(r)) * r)
conj = gr.conjugate_cc()
mixer = gr.multiply_cc()
mix_delay = delay(gr.sizeof_gr_complex, fft_length / 2 + 1)
mix_diff = gr.sub_cc()
nominator = accumulator_cc()
inpdelay = delay(gr.sizeof_gr_complex, fft_length / 2)
self.connect(self.input, inpdelay, conj, (mixer, 0))
self.connect(self.input, (mixer, 1))
self.connect(mixer, (mix_diff, 0))
self.connect(mixer, mix_delay, (mix_diff, 1))
self.connect(mix_diff, nominator)
rmagsqrd = gr.complex_to_mag_squared()
rm_delay = delay(gr.sizeof_float, fft_length + 1)
rm_diff = gr.sub_ff()
denom = accumulator_ff()
self.connect(self.input, rmagsqrd, rm_diff, gr.multiply_const_ff(0.5),
denom)
self.connect(rmagsqrd, rm_delay, (rm_diff, 1))
ps = gr.complex_to_mag_squared()
rs = gr.multiply_ff()
self.connect(nominator, ps)
self.connect(denom, rs)
self.connect(denom, (rs, 1))
div = gr.divide_ff()
self.connect(ps, div)
self.connect(rs, (div, 1))
self.connect(div, self)
def __init__(self, fg, audio_rate):
self.input_node = gr.add_const_ff(0) # FIXME kludge
self.low_iir = gr.iir_filter_ffd((0.0193,0,-0.0193),(1,1.9524,-0.9615))
self.low_square = gr.multiply_ff()
self.low_smooth = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate)) # 100ms time constant
self.hi_iir = gr.iir_filter_ffd((0.0193,0,-0.0193),(1,1.3597,-0.9615))
self.hi_square = gr.multiply_ff()
self.hi_smooth = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate))
self.sub = gr.sub_ff();
self.add = gr.add_ff();
self.gate = gr.threshold_ff(0.3,0.43,0)
self.squelch_lpf = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate))
self.div = gr.divide_ff()
self.squelch_mult = gr.multiply_ff()
fg.connect (self.input_node, (self.squelch_mult, 0))
fg.connect (self.input_node,self.low_iir)
fg.connect (self.low_iir,(self.low_square,0))
fg.connect (self.low_iir,(self.low_square,1))
fg.connect (self.low_square,self.low_smooth,(self.sub,0))
fg.connect (self.low_smooth, (self.add,0))
fg.connect (self.input_node,self.hi_iir)
fg.connect (self.hi_iir,(self.hi_square,0))
fg.connect (self.hi_iir,(self.hi_square,1))
fg.connect (self.hi_square,self.hi_smooth,(self.sub,1))
fg.connect (self.hi_smooth, (self.add,1))
fg.connect (self.sub, (self.div, 0))
fg.connect (self.add, (self.div, 1))
fg.connect (self.div, self.gate, self.squelch_lpf, (self.squelch_mult,1))
gr.hier_block.__init__(self, fg, self.input_node, self.squelch_mult)
def __init__( self ):
gr.hier_block2.__init__(self, "agc",
gr.io_signature(1,1,gr.sizeof_float),
gr.io_signature(1,1,gr.sizeof_float))
self.split = gr.multiply_const_ff( 1 )
self.sqr = gr.multiply_ff( )
self.int0 = gr.iir_filter_ffd( [.004, 0], [0, .999] )
self.offs = gr.add_const_ff( -30 )
self.gain = gr.multiply_const_ff( 70 )
self.log = gr.nlog10_ff( 10, 1 )
self.agc = gr.divide_ff( )
self.connect(self, self.split)
self.connect(self.split, (self.agc, 0))
self.connect(self.split, (self.sqr, 0))
self.connect(self.split, (self.sqr, 1))
self.connect(self.sqr, self.int0)
self.connect(self.int0, self.log)
self.connect(self.log, self.offs)
self.connect(self.offs, self.gain)
self.connect(self.gain, (self.agc, 1))
self.connect(self.agc, self)
def __init__(self):
gr.hier_block2.__init__(self, "agc",
gr.io_signature(1, 1, gr.sizeof_float),
gr.io_signature(1, 1, gr.sizeof_float))
self.split = gr.multiply_const_ff(1)
self.sqr = gr.multiply_ff()
self.int0 = gr.iir_filter_ffd([.004, 0], [0, .999])
self.offs = gr.add_const_ff(-30)
self.gain = gr.multiply_const_ff(70)
self.log = gr.nlog10_ff(10, 1)
self.agc = gr.divide_ff()
self.connect(self, self.split)
self.connect(self.split, (self.agc, 0))
self.connect(self.split, (self.sqr, 0))
self.connect(self.split, (self.sqr, 1))
self.connect(self.sqr, self.int0)
self.connect(self.int0, self.log)
self.connect(self.log, self.offs)
self.connect(self.offs, self.gain)
self.connect(self.gain, (self.agc, 1))
self.connect(self.agc, self)
def __init__(self, fft_length, pn_weights):
gr.hier_block2.__init__(self, "modified_timing_metric",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_float))
assert (len(pn_weights) == fft_length)
self.input = gr.kludge_copy(gr.sizeof_gr_complex)
self.connect(self, self.input)
# P(d) = sum(0 to L-1, conj(delayed(r)) * r)
conj = gr.conjugate_cc()
mixer = gr.multiply_cc()
nominator = gr.fir_filter_ccf(1, [
pn_weights[fft_length - i - 1] * pn_weights[fft_length / 2 - i - 1]
for i in range(fft_length / 2)
])
self.connect(self.input, delay(gr.sizeof_gr_complex, fft_length / 2),
conj, (mixer, 0))
self.connect(self.input, (mixer, 1))
self.connect(mixer, nominator)
# moving_avg = P(d)
# R(d)
denominator = schmidl_denominator(fft_length)
# |P(d)| ** 2 / (R(d)) ** 2
p_mag_sqrd = gr.complex_to_mag_squared()
r_sqrd = gr.multiply_ff()
self.timing_metric = gr.divide_ff()
self.connect(nominator, p_mag_sqrd, (self.timing_metric, 0))
self.connect(self.input, denominator, (r_sqrd, 0))
self.connect(denominator, (r_sqrd, 1))
self.connect(r_sqrd, (self.timing_metric, 1))
self.connect(self.timing_metric, self)
def __init__(self, fft_length):
gr.hier_block2.__init__(self, "timing_metric",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_float))
self.input = gr.kludge_copy(gr.sizeof_gr_complex)
self.connect(self, self.input)
# P(d)
nominator = schmidl_nominator(fft_length)
# R(d)
denominator = schmidl_denominator(fft_length)
# |P(d)| ** 2 / (R(d)) ** 2
p_mag_sqrd = gr.complex_to_mag_squared()
r_sqrd = gr.multiply_ff()
self.timing_metric = gr.divide_ff()
self.connect(self.input, nominator, p_mag_sqrd,
(self.timing_metric, 0))
self.connect(self.input, denominator, (r_sqrd, 0))
self.connect(denominator, (r_sqrd, 1))
self.connect(r_sqrd, (self.timing_metric, 1))
self.connect(self.timing_metric, self)
# calculate epsilon from P(d), epsilon is normalized fractional frequency offset
#angle = gr.complex_to_arg()
#self.epsilon = gr.multiply_const_ff(1.0/math.pi)
#self.connect(nominator, angle, self.epsilon)
try:
gr.hier_block.update_var_names(self, "schmidl", vars())
gr.hier_block.update_var_names(self, "schmidl", vars(self))
except:
pass
def __init__(self):
grc_wxgui.top_block_gui.__init__(self, title="Ofdm Rx")
##################################################
# Variables
##################################################
self.window_size = window_size = 48
self.sync_length = sync_length = 320 - 64
self.samp_rate = samp_rate = 10e6
self.gain = gain = 0
self.freq = freq = 5.825e9
##################################################
# Blocks
##################################################
self._samp_rate_chooser = forms.radio_buttons(
parent=self.GetWin(),
value=self.samp_rate,
callback=self.set_samp_rate,
label="Sample Rate",
choices=[10e6, 20e6],
labels=["10 Mhz", "20 Mhz"],
style=wx.RA_HORIZONTAL,
)
self.Add(self._samp_rate_chooser)
_gain_sizer = wx.BoxSizer(wx.VERTICAL)
self._gain_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_gain_sizer,
value=self.gain,
callback=self.set_gain,
label='gain',
converter=forms.float_converter(),
proportion=0,
)
self._gain_slider = forms.slider(
parent=self.GetWin(),
sizer=_gain_sizer,
value=self.gain,
callback=self.set_gain,
minimum=0,
maximum=100,
num_steps=100,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.Add(_gain_sizer)
self._freq_chooser = forms.drop_down(
parent=self.GetWin(),
value=self.freq,
callback=self.set_freq,
label="Channel",
choices=[2412000000.0, 2417000000.0, 2422000000.0, 2427000000.0, 2432000000.0, 2437000000.0, 2442000000.0, 2447000000.0, 2452000000.0, 2457000000.0, 2462000000.0, 2467000000.0, 2472000000.0, 2484000000.0, 5170000000.0, 5180000000.0, 5190000000.0, 5200000000.0, 5210000000.0, 5220000000.0, 5230000000.0, 5240000000.0, 5260000000.0, 5280000000.0, 5300000000.0, 5320000000.0, 5500000000.0, 5520000000.0, 5540000000.0, 5560000000.0, 5580000000.0, 5600000000.0, 5620000000.0, 5640000000.0, 5660000000.0, 5680000000.0, 5700000000.0, 5745000000.0, 5765000000.0, 5785000000.0, 5805000000.0, 5825000000.0, 5860000000.0, 5870000000.0, 5880000000.0, 5890000000.0, 5900000000.0, 5910000000.0, 5920000000.0],
labels=[' 1 | 2412.0 | 11g', ' 2 | 2417.0 | 11g', ' 3 | 2422.0 | 11g', ' 4 | 2427.0 | 11g', ' 5 | 2432.0 | 11g', ' 6 | 2437.0 | 11g', ' 7 | 2442.0 | 11g', ' 8 | 2447.0 | 11g', ' 9 | 2452.0 | 11g', ' 10 | 2457.0 | 11g', ' 11 | 2462.0 | 11g', ' 12 | 2467.0 | 11g', ' 13 | 2472.0 | 11g', ' 14 | 2484.0 | 11g', ' 34 | 5170.0 | 11a', ' 36 | 5180.0 | 11a', ' 38 | 5190.0 | 11a', ' 40 | 5200.0 | 11a', ' 42 | 5210.0 | 11a', ' 44 | 5220.0 | 11a', ' 46 | 5230.0 | 11a', ' 48 | 5240.0 | 11a', ' 52 | 5260.0 | 11a', ' 56 | 5280.0 | 11a', ' 58 | 5300.0 | 11a', ' 60 | 5320.0 | 11a', '100 | 5500.0 | 11a', '104 | 5520.0 | 11a', '108 | 5540.0 | 11a', '112 | 5560.0 | 11a', '116 | 5580.0 | 11a', '120 | 5600.0 | 11a', '124 | 5620.0 | 11a', '128 | 5640.0 | 11a', '132 | 5660.0 | 11a', '136 | 5680.0 | 11a', '140 | 5700.0 | 11a', '149 | 5745.0 | 11a', '153 | 5765.0 | 11a', '157 | 5785.0 | 11a', '161 | 5805.0 | 11a', '165 | 5825.0 | 11a', '172 | 5860.0 | 11p', '174 | 5870.0 | 11p', '176 | 5880.0 | 11p', '178 | 5890.0 | 11p', '180 | 5900.0 | 11p', '182 | 5910.0 | 11p', '184 | 5920.0 | 11p'],
)
self.Add(self._freq_chooser)
self.uhd_usrp_source_0 = uhd.usrp_source(
device_addr="",
stream_args=uhd.stream_args(
cpu_format="fc32",
channels=range(1),
),
)
self.uhd_usrp_source_0.set_samp_rate(samp_rate)
self.uhd_usrp_source_0.set_center_freq(freq, 0)
self.uhd_usrp_source_0.set_gain(gain, 0)
self.ieee802_1_ofdm_sync_short_0 = gr_ieee802_11.ofdm_sync_short(0.8, 80 * 80, 2, False)
self.ieee802_1_ofdm_sync_long_0 = gr_ieee802_11.ofdm_sync_long(sync_length, 100, False)
self.ieee802_1_ofdm_equalize_symbols_0 = gr_ieee802_11.ofdm_equalize_symbols(False)
self.ieee802_1_ofdm_decode_signal_0 = gr_ieee802_11.ofdm_decode_signal(False)
self.ieee802_1_ofdm_decode_mac_0 = gr_ieee802_11.ofdm_decode_mac(False)
self.ieee802_11_ofdm_parse_mac_0 = gr_ieee802_11.ofdm_parse_mac(True)
self.gr_stream_to_vector_0 = gr.stream_to_vector(gr.sizeof_gr_complex*1, 64)
self.gr_socket_pdu_0 = gr.socket_pdu("UDP_SERVER", "", "12345", 10000)
self.gr_skiphead_0 = gr.skiphead(gr.sizeof_gr_complex*1, 20000000)
self.gr_multiply_xx_0 = gr.multiply_vcc(1)
self.gr_divide_xx_0 = gr.divide_ff(1)
self.gr_delay_0_0 = gr.delay(gr.sizeof_gr_complex*1, sync_length)
self.gr_delay_0 = gr.delay(gr.sizeof_gr_complex*1, 16)
self.gr_conjugate_cc_0 = gr.conjugate_cc()
self.gr_complex_to_mag_squared_0 = gr.complex_to_mag_squared(1)
self.gr_complex_to_mag_0 = gr.complex_to_mag(1)
self.fir_filter_xxx_0_0 = filter.fir_filter_ccf(1, ([1]*window_size))
self.fir_filter_xxx_0 = filter.fir_filter_fff(1, ([1]*window_size))
self.fft_vxx_0 = fft.fft_vcc(64, True, (), True, 1)
##################################################
# Connections
##################################################
self.connect((self.uhd_usrp_source_0, 0), (self.gr_skiphead_0, 0))
self.connect((self.gr_skiphead_0, 0), (self.gr_complex_to_mag_squared_0, 0))
self.connect((self.fir_filter_xxx_0, 0), (self.gr_divide_xx_0, 1))
self.connect((self.gr_complex_to_mag_squared_0, 0), (self.fir_filter_xxx_0, 0))
self.connect((self.gr_skiphead_0, 0), (self.gr_multiply_xx_0, 0))
self.connect((self.gr_conjugate_cc_0, 0), (self.gr_multiply_xx_0, 1))
self.connect((self.gr_complex_to_mag_0, 0), (self.gr_divide_xx_0, 0))
self.connect((self.gr_multiply_xx_0, 0), (self.fir_filter_xxx_0_0, 0))
self.connect((self.fir_filter_xxx_0_0, 0), (self.gr_complex_to_mag_0, 0))
self.connect((self.gr_skiphead_0, 0), (self.gr_delay_0, 0))
self.connect((self.gr_delay_0, 0), (self.gr_conjugate_cc_0, 0))
self.connect((self.fft_vxx_0, 0), (self.ieee802_1_ofdm_equalize_symbols_0, 0))
self.connect((self.ieee802_1_ofdm_equalize_symbols_0, 0), (self.ieee802_1_ofdm_decode_signal_0, 0))
self.connect((self.ieee802_1_ofdm_decode_signal_0, 0), (self.ieee802_1_ofdm_decode_mac_0, 0))
self.connect((self.ieee802_1_ofdm_sync_short_0, 0), (self.gr_delay_0_0, 0))
self.connect((self.gr_delay_0, 0), (self.ieee802_1_ofdm_sync_short_0, 0))
self.connect((self.gr_divide_xx_0, 0), (self.ieee802_1_ofdm_sync_short_0, 1))
self.connect((self.gr_delay_0_0, 0), (self.ieee802_1_ofdm_sync_long_0, 1))
self.connect((self.ieee802_1_ofdm_sync_short_0, 0), (self.ieee802_1_ofdm_sync_long_0, 0))
self.connect((self.ieee802_1_ofdm_sync_long_0, 0), (self.gr_stream_to_vector_0, 0))
self.connect((self.gr_stream_to_vector_0, 0), (self.fft_vxx_0, 0))
##################################################
# Asynch Message Connections
##################################################
self.msg_connect(self.ieee802_1_ofdm_decode_mac_0, "out", self.ieee802_11_ofdm_parse_mac_0, "in")
self.msg_connect(self.ieee802_11_ofdm_parse_mac_0, "out", self.gr_socket_pdu_0, "pdus")
def test_div_ff_1 (self):
src1_data = (1, 2, 4, -8)
expected_result = (1, 0.5, 0.25, -.125)
op = gr.divide_ff (1)
self.help_ff ((src1_data,),
expected_result, op, port_prefix='SINGLE_PORT')
def __init__(self, *args, **kwds):
# begin wxGlade: MyFrame.__init__
kwds["style"] = wx.DEFAULT_FRAME_STYLE
wx.Frame.__init__(self, *args, **kwds)
# Menu Bar
self.frame_1_menubar = wx.MenuBar()
self.SetMenuBar(self.frame_1_menubar)
wxglade_tmp_menu = wx.Menu()
self.Exit = wx.MenuItem(wxglade_tmp_menu, ID_EXIT, "Exit", "Exit",
wx.ITEM_NORMAL)
wxglade_tmp_menu.AppendItem(self.Exit)
self.frame_1_menubar.Append(wxglade_tmp_menu, "File")
# Menu Bar end
self.panel_1 = wx.Panel(self, -1)
self.button_1 = wx.Button(self, ID_BUTTON_1, "LSB")
self.button_2 = wx.Button(self, ID_BUTTON_2, "USB")
self.button_3 = wx.Button(self, ID_BUTTON_3, "AM")
self.button_4 = wx.Button(self, ID_BUTTON_4, "CW")
self.button_5 = wx.ToggleButton(self, ID_BUTTON_5, "Upper")
self.slider_fcutoff_hi = wx.Slider(self,
ID_SLIDER_1,
0,
-15798,
15799,
style=wx.SL_HORIZONTAL
| wx.SL_LABELS)
self.button_6 = wx.ToggleButton(self, ID_BUTTON_6, "Lower")
self.slider_fcutoff_lo = wx.Slider(self,
ID_SLIDER_2,
0,
-15799,
15798,
style=wx.SL_HORIZONTAL
| wx.SL_LABELS)
self.panel_5 = wx.Panel(self, -1)
self.label_1 = wx.StaticText(self, -1, " Band\nCenter")
self.text_ctrl_1 = wx.TextCtrl(self, ID_TEXT_1, "")
self.panel_6 = wx.Panel(self, -1)
self.panel_7 = wx.Panel(self, -1)
self.panel_2 = wx.Panel(self, -1)
self.button_7 = wx.ToggleButton(self, ID_BUTTON_7, "Freq")
self.slider_3 = wx.Slider(self, ID_SLIDER_3, 3000, 0, 6000)
self.spin_ctrl_1 = wx.SpinCtrl(self, ID_SPIN_1, "", min=0, max=100)
self.button_8 = wx.ToggleButton(self, ID_BUTTON_8, "Vol")
self.slider_4 = wx.Slider(self, ID_SLIDER_4, 0, 0, 500)
self.slider_5 = wx.Slider(self, ID_SLIDER_5, 0, 0, 20)
self.button_9 = wx.ToggleButton(self, ID_BUTTON_9, "Time")
self.button_11 = wx.Button(self, ID_BUTTON_11, "Rew")
self.button_10 = wx.Button(self, ID_BUTTON_10, "Fwd")
self.panel_3 = wx.Panel(self, -1)
self.label_2 = wx.StaticText(self, -1, "PGA ")
self.panel_4 = wx.Panel(self, -1)
self.panel_8 = wx.Panel(self, -1)
self.panel_9 = wx.Panel(self, -1)
self.label_3 = wx.StaticText(self, -1, "AM Sync\nCarrier")
self.slider_6 = wx.Slider(self,
ID_SLIDER_6,
50,
0,
200,
style=wx.SL_HORIZONTAL | wx.SL_LABELS)
self.label_4 = wx.StaticText(self, -1, "Antenna Tune")
self.slider_7 = wx.Slider(self,
ID_SLIDER_7,
1575,
950,
2200,
style=wx.SL_HORIZONTAL | wx.SL_LABELS)
self.panel_10 = wx.Panel(self, -1)
self.button_12 = wx.ToggleButton(self, ID_BUTTON_12, "Auto Tune")
self.button_13 = wx.Button(self, ID_BUTTON_13, "Calibrate")
self.button_14 = wx.Button(self, ID_BUTTON_14, "Reset")
self.panel_11 = wx.Panel(self, -1)
self.panel_12 = wx.Panel(self, -1)
self.__set_properties()
self.__do_layout()
# end wxGlade
parser = OptionParser(option_class=eng_option)
parser.add_option("",
"--address",
type="string",
default="addr=192.168.10.2",
help="Address of UHD device, [default=%default]")
parser.add_option("-c",
"--ddc-freq",
type="eng_float",
default=3.9e6,
help="set Rx DDC frequency to FREQ",
metavar="FREQ")
parser.add_option(
"-s",
"--samp-rate",
type="eng_float",
default=256e3,
help="set sample rate (bandwidth) [default=%default]")
parser.add_option("-a",
"--audio_file",
default="",
help="audio output file",
metavar="FILE")
parser.add_option("-r",
"--radio_file",
default="",
help="radio output file",
metavar="FILE")
parser.add_option("-i",
"--input_file",
default="",
help="radio input file",
metavar="FILE")
parser.add_option(
"-O",
"--audio-output",
type="string",
default="",
help="audio output device name. E.g., hw:0,0, /dev/dsp, or pulse")
(options, args) = parser.parse_args()
self.usrp_center = options.ddc_freq
input_rate = options.samp_rate
self.slider_range = input_rate * 0.9375
self.f_lo = self.usrp_center - (self.slider_range / 2)
self.f_hi = self.usrp_center + (self.slider_range / 2)
self.af_sample_rate = 32000
fir_decim = long(input_rate / self.af_sample_rate)
# data point arrays for antenna tuner
self.xdata = []
self.ydata = []
self.tb = gr.top_block()
# radio variables, initial conditions
self.frequency = self.usrp_center
# these map the frequency slider (0-6000) to the actual range
self.f_slider_offset = self.f_lo
self.f_slider_scale = 10000
self.spin_ctrl_1.SetRange(self.f_lo, self.f_hi)
self.text_ctrl_1.SetValue(str(int(self.usrp_center)))
self.slider_5.SetValue(0)
self.AM_mode = False
self.slider_3.SetValue(
(self.frequency - self.f_slider_offset) / self.f_slider_scale)
self.spin_ctrl_1.SetValue(int(self.frequency))
POWERMATE = True
try:
self.pm = powermate.powermate(self)
except:
sys.stderr.write("Unable to find PowerMate or Contour Shuttle\n")
POWERMATE = False
if POWERMATE:
powermate.EVT_POWERMATE_ROTATE(self, self.on_rotate)
powermate.EVT_POWERMATE_BUTTON(self, self.on_pmButton)
self.active_button = 7
# command line options
if options.audio_file == "": SAVE_AUDIO_TO_FILE = False
else: SAVE_AUDIO_TO_FILE = True
if options.radio_file == "": SAVE_RADIO_TO_FILE = False
else: SAVE_RADIO_TO_FILE = True
if options.input_file == "": self.PLAY_FROM_USRP = True
else: self.PLAY_FROM_USRP = False
if self.PLAY_FROM_USRP:
self.src = uhd.usrp_source(device_addr=options.address,
io_type=uhd.io_type.COMPLEX_FLOAT32,
num_channels=1)
self.src.set_samp_rate(input_rate)
input_rate = self.src.get_samp_rate()
self.src.set_center_freq(self.usrp_center, 0)
self.tune_offset = 0
else:
self.src = gr.file_source(gr.sizeof_short, options.input_file)
self.tune_offset = 2200 # 2200 works for 3.5-4Mhz band
# convert rf data in interleaved short int form to complex
s2ss = gr.stream_to_streams(gr.sizeof_short, 2)
s2f1 = gr.short_to_float()
s2f2 = gr.short_to_float()
src_f2c = gr.float_to_complex()
self.tb.connect(self.src, s2ss)
self.tb.connect((s2ss, 0), s2f1)
self.tb.connect((s2ss, 1), s2f2)
self.tb.connect(s2f1, (src_f2c, 0))
self.tb.connect(s2f2, (src_f2c, 1))
# save radio data to a file
if SAVE_RADIO_TO_FILE:
radio_file = gr.file_sink(gr.sizeof_short, options.radio_file)
self.tb.connect(self.src, radio_file)
# 2nd DDC
xlate_taps = gr.firdes.low_pass ( \
1.0, input_rate, 16e3, 4e3, gr.firdes.WIN_HAMMING )
self.xlate = gr.freq_xlating_fir_filter_ccf ( \
fir_decim, xlate_taps, self.tune_offset, input_rate )
# Complex Audio filter
audio_coeffs = gr.firdes.complex_band_pass(
1.0, # gain
self.af_sample_rate, # sample rate
-3000, # low cutoff
0, # high cutoff
100, # transition
gr.firdes.WIN_HAMMING) # window
self.slider_fcutoff_hi.SetValue(0)
self.slider_fcutoff_lo.SetValue(-3000)
self.audio_filter = gr.fir_filter_ccc(1, audio_coeffs)
# Main +/- 16Khz spectrum display
self.fft = fftsink2.fft_sink_c(self.panel_2,
fft_size=512,
sample_rate=self.af_sample_rate,
average=True,
size=(640, 240))
# AM Sync carrier
if AM_SYNC_DISPLAY:
self.fft2 = fftsink.fft_sink_c(self.tb,
self.panel_9,
y_per_div=20,
fft_size=512,
sample_rate=self.af_sample_rate,
average=True,
size=(640, 240))
c2f = gr.complex_to_float()
# AM branch
self.sel_am = gr.multiply_const_cc(0)
# the following frequencies turn out to be in radians/sample
# gr.pll_refout_cc(alpha,beta,min_freq,max_freq)
# suggested alpha = X, beta = .25 * X * X
pll = gr.pll_refout_cc(.5, .0625,
(2. * math.pi * 7.5e3 / self.af_sample_rate),
(2. * math.pi * 6.5e3 / self.af_sample_rate))
self.pll_carrier_scale = gr.multiply_const_cc(complex(10, 0))
am_det = gr.multiply_cc()
# these are for converting +7.5kHz to -7.5kHz
# for some reason gr.conjugate_cc() adds noise ??
c2f2 = gr.complex_to_float()
c2f3 = gr.complex_to_float()
f2c = gr.float_to_complex()
phaser1 = gr.multiply_const_ff(1)
phaser2 = gr.multiply_const_ff(-1)
# filter for pll generated carrier
pll_carrier_coeffs = gr.firdes.complex_band_pass(
2.0, # gain
self.af_sample_rate, # sample rate
7400, # low cutoff
7600, # high cutoff
100, # transition
gr.firdes.WIN_HAMMING) # window
self.pll_carrier_filter = gr.fir_filter_ccc(1, pll_carrier_coeffs)
self.sel_sb = gr.multiply_const_ff(1)
combine = gr.add_ff()
#AGC
sqr1 = gr.multiply_ff()
intr = gr.iir_filter_ffd([.004, 0], [0, .999])
offset = gr.add_const_ff(1)
agc = gr.divide_ff()
self.scale = gr.multiply_const_ff(0.00001)
dst = audio.sink(long(self.af_sample_rate), options.audio_output)
if self.PLAY_FROM_USRP:
self.tb.connect(self.src, self.xlate, self.fft)
else:
self.tb.connect(src_f2c, self.xlate, self.fft)
self.tb.connect(self.xlate, self.audio_filter, self.sel_am,
(am_det, 0))
self.tb.connect(self.sel_am, pll, self.pll_carrier_scale,
self.pll_carrier_filter, c2f3)
self.tb.connect((c2f3, 0), phaser1, (f2c, 0))
self.tb.connect((c2f3, 1), phaser2, (f2c, 1))
self.tb.connect(f2c, (am_det, 1))
self.tb.connect(am_det, c2f2, (combine, 0))
self.tb.connect(self.audio_filter, c2f, self.sel_sb, (combine, 1))
if AM_SYNC_DISPLAY:
self.tb.connect(self.pll_carrier_filter, self.fft2)
self.tb.connect(combine, self.scale)
self.tb.connect(self.scale, (sqr1, 0))
self.tb.connect(self.scale, (sqr1, 1))
self.tb.connect(sqr1, intr, offset, (agc, 1))
self.tb.connect(self.scale, (agc, 0))
self.tb.connect(agc, dst)
if SAVE_AUDIO_TO_FILE:
f_out = gr.file_sink(gr.sizeof_short, options.audio_file)
sc1 = gr.multiply_const_ff(64000)
f2s1 = gr.float_to_short()
self.tb.connect(agc, sc1, f2s1, f_out)
self.tb.start()
# for mouse position reporting on fft display
self.fft.win.Bind(wx.EVT_LEFT_UP, self.Mouse)
# and left click to re-tune
self.fft.win.Bind(wx.EVT_LEFT_DOWN, self.Click)
# start a timer to check for web commands
if WEB_CONTROL:
self.timer = UpdateTimer(self, 1000) # every 1000 mSec, 1 Sec
wx.EVT_BUTTON(self, ID_BUTTON_1, self.set_lsb)
wx.EVT_BUTTON(self, ID_BUTTON_2, self.set_usb)
wx.EVT_BUTTON(self, ID_BUTTON_3, self.set_am)
wx.EVT_BUTTON(self, ID_BUTTON_4, self.set_cw)
wx.EVT_BUTTON(self, ID_BUTTON_10, self.fwd)
wx.EVT_BUTTON(self, ID_BUTTON_11, self.rew)
wx.EVT_BUTTON(self, ID_BUTTON_13, self.AT_calibrate)
wx.EVT_BUTTON(self, ID_BUTTON_14, self.AT_reset)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_5, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_6, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_7, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_8, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_9, self.on_button)
wx.EVT_SLIDER(self, ID_SLIDER_1, self.set_filter)
wx.EVT_SLIDER(self, ID_SLIDER_2, self.set_filter)
wx.EVT_SLIDER(self, ID_SLIDER_3, self.slide_tune)
wx.EVT_SLIDER(self, ID_SLIDER_4, self.set_volume)
wx.EVT_SLIDER(self, ID_SLIDER_5, self.set_pga)
wx.EVT_SLIDER(self, ID_SLIDER_6, self.am_carrier)
wx.EVT_SLIDER(self, ID_SLIDER_7, self.antenna_tune)
wx.EVT_SPINCTRL(self, ID_SPIN_1, self.spin_tune)
wx.EVT_MENU(self, ID_EXIT, self.TimeToQuit)
def __init__(self, vlen):
gr.hier_block2.__init__(self, "snr_estimator",
gr.io_signature2(2,2,gr.sizeof_gr_complex,gr.sizeof_char),
gr.io_signature (1,1,gr.sizeof_float))
data_in = (self,0)
trig_in = (self,1)
snr_out = (self,0)
## Preamble Extraction
sampler = vector_sampler(gr.sizeof_gr_complex,vlen)
self.connect(data_in,sampler)
self.connect(trig_in,(sampler,1))
## Algorithm implementation
estim = sc_snr_estimator(vlen)
self.connect(sampler,estim)
self.connect(estim,snr_out)
return
## Split block into two parts
splitter = gr.vector_to_streams(gr.sizeof_gr_complex*vlen/2,2)
self.connect(sampler,splitter)
## Conjugate first half block
conj = gr.conjugate_cc(vlen/2)
self.connect(splitter,conj)
## Vector multiplication of both half blocks
vmult = gr.multiply_vcc(vlen/2)
self.connect(conj,vmult)
self.connect((splitter,1),(vmult,1))
## Sum of Products
psum = vector_sum_vcc(vlen/2)
self.connect(vmult,psum)
## Magnitude of P(d)
p_mag = gr.complex_to_mag()
self.connect(psum,p_mag)
## Squared Magnitude of block
r_magsqrd = gr.complex_to_mag_squared(vlen)
self.connect(sampler,r_magsqrd)
## Sum of squared second half block
r_sum = vector_sum_vff(vlen)
self.connect(r_magsqrd,r_sum)
## Square Root of Metric
m_sqrt = gr.divide_ff()
self.connect(p_mag,(m_sqrt,0))
self.connect(r_sum,gr.multiply_const_ff(0.5),(m_sqrt,1))
## Denominator of SNR estimate
denom = gr.add_const_ff(1)
neg_m_sqrt = gr.multiply_const_ff(-1.0)
self.connect(m_sqrt,limit_vff(1,1-2e-5,-1000),neg_m_sqrt,denom)
## SNR estimate
snr_est = gr.divide_ff()
self.connect(m_sqrt,(snr_est,0))
self.connect(denom,(snr_est,1))
## Setup Output Connections
self.connect(snr_est,self)
def __init__(self, freq_corr=0, N_id_1=134, avg_frames=1, N_id_2=0, decim=16): grc_wxgui.top_block_gui.__init__(self, title="Sss Corr2 Gui") _icon_path = "/usr/share/icons/hicolor/32x32/apps/gnuradio-grc.png" self.SetIcon(wx.Icon(_icon_path, wx.BITMAP_TYPE_ANY)) ################################################## # Parameters ################################################## self.freq_corr = freq_corr self.N_id_1 = N_id_1 self.avg_frames = avg_frames self.N_id_2 = N_id_2 self.decim = decim ################################################## # Variables ################################################## self.vec_half_frame = vec_half_frame = 30720*5/decim self.samp_rate = samp_rate = 30720e3/decim self.rot = rot = 0 self.noise_level = noise_level = 0 self.fft_size = fft_size = 2048/decim ################################################## # Blocks ################################################## _rot_sizer = wx.BoxSizer(wx.VERTICAL) self._rot_text_box = forms.text_box( parent=self.GetWin(), sizer=_rot_sizer, value=self.rot, callback=self.set_rot, label='rot', converter=forms.float_converter(), proportion=0, ) self._rot_slider = forms.slider( parent=self.GetWin(), sizer=_rot_sizer, value=self.rot, callback=self.set_rot, minimum=0, maximum=1, num_steps=100, style=wx.SL_HORIZONTAL, cast=float, proportion=1, ) self.Add(_rot_sizer) _noise_level_sizer = wx.BoxSizer(wx.VERTICAL) self._noise_level_text_box = forms.text_box( parent=self.GetWin(), sizer=_noise_level_sizer, value=self.noise_level, callback=self.set_noise_level, label='noise_level', converter=forms.float_converter(), proportion=0, ) self._noise_level_slider = forms.slider( parent=self.GetWin(), sizer=_noise_level_sizer, value=self.noise_level, callback=self.set_noise_level, minimum=0, maximum=10, num_steps=100, style=wx.SL_HORIZONTAL, cast=float, proportion=1, ) self.Add(_noise_level_sizer) self.wxgui_scopesink2_0 = scopesink2.scope_sink_c( self.GetWin(), title="Scope Plot", sample_rate=samp_rate, v_scale=0, v_offset=0, t_scale=0, ac_couple=False, xy_mode=False, num_inputs=2, trig_mode=gr.gr_TRIG_MODE_AUTO, y_axis_label="Counts", ) self.Add(self.wxgui_scopesink2_0.win) self.gr_vector_to_stream_1 = gr.vector_to_stream(gr.sizeof_gr_complex*1, fft_size) self.gr_vector_to_stream_0_2 = gr.vector_to_stream(gr.sizeof_gr_complex*1, fft_size) self.gr_vector_to_stream_0_1 = gr.vector_to_stream(gr.sizeof_gr_complex*1, fft_size) self.gr_vector_to_stream_0_0 = gr.vector_to_stream(gr.sizeof_gr_complex*1, fft_size) self.gr_vector_to_stream_0 = gr.vector_to_stream(gr.sizeof_float*1, fft_size) self.gr_vector_source_x_0_0_0 = gr.vector_source_c((gen_pss_fd(N_id_2, fft_size, False).get_data()), True, fft_size) self.gr_vector_source_x_0_0 = gr.vector_source_c((gen_pss_fd(N_id_2, fft_size, False).get_data()), True, fft_size) self.gr_vector_source_x_0 = gr.vector_source_c((gen_sss_fd( N_id_1, N_id_2, fft_size).get_sss(True)), True, fft_size) self.gr_stream_to_vector_0_0 = gr.stream_to_vector(gr.sizeof_gr_complex*1, fft_size) self.gr_stream_to_vector_0 = gr.stream_to_vector(gr.sizeof_gr_complex*1, fft_size) self.gr_repeat_0 = gr.repeat(gr.sizeof_float*1, fft_size) self.gr_null_sink_0_0 = gr.null_sink(gr.sizeof_gr_complex*1) self.gr_null_sink_0 = gr.null_sink(gr.sizeof_gr_complex*1) self.gr_noise_source_x_0 = gr.noise_source_c(gr.GR_GAUSSIAN, noise_level, 0) self.gr_multiply_xx_1 = gr.multiply_vcc(1) self.gr_multiply_xx_0 = gr.multiply_vcc(fft_size) self.gr_multiply_const_vxx_1 = gr.multiply_const_vcc((1/1500., )) self.gr_multiply_const_vxx_0 = gr.multiply_const_vcc((exp(rot*2*numpy.pi*1j), )) self.gr_interleave_0 = gr.interleave(gr.sizeof_gr_complex*fft_size) self.gr_integrate_xx_0 = gr.integrate_ff(fft_size) self.gr_float_to_complex_0_0 = gr.float_to_complex(1) self.gr_float_to_complex_0 = gr.float_to_complex(1) self.gr_file_source_0 = gr.file_source(gr.sizeof_gr_complex*1, "/home/user/git/gr-lte/gr-lte/test/foo_pss0_sss_in.cfile", True) self.gr_fft_vxx_1 = gr.fft_vcc(fft_size, False, (window.blackmanharris(1024)), True, 1) self.gr_fft_vxx_0 = gr.fft_vcc(fft_size, True, (window.blackmanharris(1024)), True, 1) self.gr_divide_xx_0_1 = gr.divide_cc(1) self.gr_divide_xx_0_0 = gr.divide_ff(1) self.gr_divide_xx_0 = gr.divide_cc(1) self.gr_deinterleave_0 = gr.deinterleave(gr.sizeof_gr_complex*fft_size) self.gr_conjugate_cc_1 = gr.conjugate_cc() self.gr_conjugate_cc_0 = gr.conjugate_cc() self.gr_complex_to_mag_squared_0_0 = gr.complex_to_mag_squared(1) self.gr_complex_to_mag_squared_0 = gr.complex_to_mag_squared(fft_size) self.gr_add_xx_0 = gr.add_vcc(1) self.gr_add_const_vxx_0 = gr.add_const_vff((1, )) self.const_source_x_0_0 = gr.sig_source_f(0, gr.GR_CONST_WAVE, 0, 0, 0) self.const_source_x_0 = gr.sig_source_f(0, gr.GR_CONST_WAVE, 0, 0, 0) ################################################## # Connections ################################################## self.connect((self.gr_file_source_0, 0), (self.gr_stream_to_vector_0, 0)) self.connect((self.gr_conjugate_cc_0, 0), (self.gr_stream_to_vector_0_0, 0)) self.connect((self.gr_stream_to_vector_0_0, 0), (self.gr_multiply_xx_0, 1)) self.connect((self.gr_deinterleave_0, 0), (self.gr_multiply_xx_0, 0)) self.connect((self.gr_multiply_xx_0, 0), (self.gr_complex_to_mag_squared_0, 0)) self.connect((self.gr_complex_to_mag_squared_0, 0), (self.gr_vector_to_stream_0, 0)) self.connect((self.gr_vector_to_stream_0, 0), (self.gr_integrate_xx_0, 0)) self.connect((self.gr_integrate_xx_0, 0), (self.gr_repeat_0, 0)) self.connect((self.gr_multiply_xx_0, 0), (self.gr_vector_to_stream_0_0, 0)) self.connect((self.gr_vector_to_stream_0_1, 0), (self.gr_multiply_xx_1, 1)) self.connect((self.gr_divide_xx_0, 0), (self.gr_multiply_xx_1, 0)) self.connect((self.gr_float_to_complex_0, 0), (self.gr_divide_xx_0, 1)) self.connect((self.gr_conjugate_cc_1, 0), (self.gr_divide_xx_0, 0)) self.connect((self.gr_deinterleave_0, 1), (self.gr_vector_to_stream_0_1, 0)) self.connect((self.gr_repeat_0, 0), (self.gr_float_to_complex_0, 0)) self.connect((self.const_source_x_0, 0), (self.gr_float_to_complex_0, 1)) self.connect((self.gr_vector_to_stream_0_0, 0), (self.gr_conjugate_cc_1, 0)) self.connect((self.gr_vector_to_stream_0_0, 0), (self.gr_complex_to_mag_squared_0_0, 0)) self.connect((self.gr_complex_to_mag_squared_0_0, 0), (self.gr_divide_xx_0_0, 0)) self.connect((self.gr_repeat_0, 0), (self.gr_divide_xx_0_0, 1)) self.connect((self.gr_divide_xx_0_0, 0), (self.gr_add_const_vxx_0, 0)) self.connect((self.gr_add_const_vxx_0, 0), (self.gr_float_to_complex_0_0, 0)) self.connect((self.const_source_x_0_0, 0), (self.gr_float_to_complex_0_0, 1)) self.connect((self.gr_float_to_complex_0_0, 0), (self.gr_divide_xx_0_1, 1)) self.connect((self.gr_multiply_xx_1, 0), (self.gr_divide_xx_0_1, 0)) self.connect((self.gr_stream_to_vector_0, 0), (self.gr_fft_vxx_0, 0)) self.connect((self.gr_fft_vxx_0, 0), (self.gr_deinterleave_0, 0)) self.connect((self.gr_vector_to_stream_0_2, 0), (self.gr_conjugate_cc_0, 0)) self.connect((self.gr_divide_xx_0_1, 0), (self.gr_null_sink_0, 0)) self.connect((self.gr_vector_source_x_0, 0), (self.gr_interleave_0, 1)) self.connect((self.gr_interleave_0, 0), (self.gr_fft_vxx_1, 0)) self.connect((self.gr_fft_vxx_1, 0), (self.gr_vector_to_stream_1, 0)) self.connect((self.gr_vector_source_x_0_0, 0), (self.gr_interleave_0, 0)) self.connect((self.gr_vector_source_x_0_0_0, 0), (self.gr_vector_to_stream_0_2, 0)) self.connect((self.gr_noise_source_x_0, 0), (self.gr_add_xx_0, 1)) self.connect((self.gr_vector_to_stream_1, 0), (self.gr_add_xx_0, 0)) self.connect((self.gr_add_xx_0, 0), (self.gr_multiply_const_vxx_0, 0)) self.connect((self.gr_vector_to_stream_0_1, 0), (self.gr_multiply_const_vxx_1, 0)) self.connect((self.gr_multiply_const_vxx_0, 0), (self.gr_null_sink_0_0, 0)) self.connect((self.gr_multiply_const_vxx_1, 0), (self.wxgui_scopesink2_0, 1)) self.connect((self.gr_divide_xx_0_1, 0), (self.wxgui_scopesink2_0, 0))
def __init__(self, fft_length, cp_length, half_sync, logging=False):
gr.hier_block2.__init__(self, "ofdm_sync_pn",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature3(3, 3, # Output signature
gr.sizeof_gr_complex, # delayed input
gr.sizeof_float, # fine frequency offset
gr.sizeof_char # timing indicator
))
if half_sync:
period = fft_length/2
window = fft_length/2
else: # full symbol
period = fft_length + cp_length
window = fft_length # makes the plateau cp_length long
# Calculate the frequency offset from the correlation of the preamble
x_corr = gr.multiply_cc()
self.connect(self, gr.conjugate_cc(), (x_corr, 0))
self.connect(self, gr.delay(gr.sizeof_gr_complex, period), (x_corr, 1))
P_d = gr.moving_average_cc(window, 1.0)
self.connect(x_corr, P_d)
P_d_angle = gr.complex_to_arg()
self.connect(P_d, P_d_angle)
# Get the power of the input signal to normalize the output of the correlation
R_d = gr.moving_average_ff(window, 1.0)
self.connect(self, gr.complex_to_mag_squared(), R_d)
R_d_squared = gr.multiply_ff() # this is retarded
self.connect(R_d, (R_d_squared, 0))
self.connect(R_d, (R_d_squared, 1))
M_d = gr.divide_ff()
self.connect(P_d, gr.complex_to_mag_squared(), (M_d, 0))
self.connect(R_d_squared, (M_d, 1))
# Now we need to detect peak of M_d
# NOTE: replaced fir_filter with moving_average for clarity
# the peak is up to cp_length long, but noisy, so average it out
#matched_filter_taps = [1.0/cp_length for i in range(cp_length)]
#matched_filter = gr.fir_filter_fff(1, matched_filter_taps)
matched_filter = gr.moving_average_ff(cp_length, 1.0/cp_length)
# NOTE: the look_ahead parameter doesn't do anything
# these parameters are kind of magic, increase 1 and 2 (==) to be more tolerant
#peak_detect = raw.peak_detector_fb(0.55, 0.55, 30, 0.001)
peak_detect = raw.peak_detector_fb(0.25, 0.25, 30, 0.001)
# NOTE: gr.peak_detector_fb is broken!
#peak_detect = gr.peak_detector_fb(0.55, 0.55, 30, 0.001)
#peak_detect = gr.peak_detector_fb(0.45, 0.45, 30, 0.001)
#peak_detect = gr.peak_detector_fb(0.30, 0.30, 30, 0.001)
# offset by -1
self.connect(M_d, matched_filter, gr.add_const_ff(-1), peak_detect)
# peak_detect indicates the time M_d is highest, which is the end of the symbol.
# We should try to sample in the middle of the plateau!!
# FIXME until we figure out how to do this, just offset by cp_length/2
offset = 6 #cp_length/2
# nco(t) = P_d_angle(t-offset) sampled at peak_detect(t)
# modulate input(t - fft_length) by nco(t)
# signal to sample input(t) at t-offset
#
# We can't delay by < 0 so instead:
# input is delayed by fft_length
# P_d_angle is delayed by offset
# signal to sample is delayed by fft_length - offset
#
phi = gr.sample_and_hold_ff()
self.connect(peak_detect, (phi,1))
self.connect(P_d_angle, gr.delay(gr.sizeof_float, offset), (phi,0))
#self.connect(P_d_angle, matched_filter2, (phi,0)) # why isn't this better?!?
# FIXME: we add fft_length delay so that the preamble is nco corrected too
# BUT is this buffering worth it? consider implementing sync as a proper block
# delay the input signal to follow the frequency offset signal
self.connect(self, gr.delay(gr.sizeof_gr_complex, (fft_length+offset)), (self,0))
self.connect(phi, (self,1))
self.connect(peak_detect, (self,2))
if logging:
self.connect(matched_filter, gr.file_sink(gr.sizeof_float, "sync-mf.dat"))
self.connect(M_d, gr.file_sink(gr.sizeof_float, "sync-M.dat"))
self.connect(P_d_angle, gr.file_sink(gr.sizeof_float, "sync-angle.dat"))
self.connect(peak_detect, gr.file_sink(gr.sizeof_char, "sync-peaks.datb"))
self.connect(phi, gr.file_sink(gr.sizeof_float, "sync-phi.dat"))
def test_div_ff_1 (self):
src1_data = (1, 2, 4, -8)
expected_result = (1, 0.5, 0.25, -.125)
op = gr.divide_ff ()
self.help_ff ((src1_data,),
expected_result, op)
def __init__(self, fft_length, cp_length, logging=False):
"""
OFDM synchronization using PN Correlation:
T. M. Schmidl and D. C. Cox, "Robust Frequency and Timing
Synchonization for OFDM," IEEE Trans. Communications, vol. 45,
no. 12, 1997.
"""
gr.hier_block2.__init__(self, "ofdm_sync_pn",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
# PN Sync
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length/2)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc();
self.corr = gr.multiply_cc();
# Create a moving sum filter for the corr output
if 1:
moving_sum_taps = [1.0 for i in range(fft_length//2)]
self.moving_sum_filter = gr.fir_filter_ccf(1,moving_sum_taps)
else:
moving_sum_taps = [complex(1.0,0.0) for i in range(fft_length//2)]
self.moving_sum_filter = gr.fft_filter_ccc(1,moving_sum_taps)
# Create a moving sum filter for the input
self.inputmag2 = gr.complex_to_mag_squared()
movingsum2_taps = [1.0 for i in range(fft_length//2)]
if 1:
self.inputmovingsum = gr.fir_filter_fff(1,movingsum2_taps)
else:
self.inputmovingsum = gr.fft_filter_fff(1,movingsum2_taps)
self.square = gr.multiply_ff()
self.normalize = gr.divide_ff()
# Get magnitude (peaks) and angle (phase/freq error)
self.c2mag = gr.complex_to_mag_squared()
self.angle = gr.complex_to_arg()
self.sample_and_hold = gr.sample_and_hold_ff()
#ML measurements input to sampler block and detect
#self.sub1 = gr.add_const_ff(-1)
self.sub1 = gr.add_const_ff(0)
self.pk_detect = gr.peak_detector_fb(0.20, 0.20, 30, 0.001)
#self.pk_detect = gr.peak_detector2_fb(9)
self.connect(self, self.input)
# Calculate the frequency offset from the correlation of the preamble
self.connect(self.input, self.delay)
self.connect(self.input, (self.corr,0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr,1))
self.connect(self.corr, self.moving_sum_filter)
self.connect(self.moving_sum_filter, self.c2mag)
self.connect(self.moving_sum_filter, self.angle)
self.connect(self.angle, (self.sample_and_hold,0))
# Get the power of the input signal to normalize the output of the correlation
self.connect(self.input, self.inputmag2, self.inputmovingsum)
self.connect(self.inputmovingsum, (self.square,0))
self.connect(self.inputmovingsum, (self.square,1))
self.connect(self.square, (self.normalize,1))
self.connect(self.c2mag, (self.normalize,0))
# Create a moving sum filter for the corr output
matched_filter_taps = [1.0/cp_length for i in range(cp_length)]
self.matched_filter = gr.fir_filter_fff(1,matched_filter_taps)
self.connect(self.normalize, self.matched_filter)
self.connect(self.matched_filter, self.sub1, self.pk_detect)
#self.connect(self.matched_filter, self.pk_detect)
self.connect(self.pk_detect, (self.sample_and_hold,1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self,0))
self.connect(self.pk_detect, (self,1))
if logging:
self.connect(self.matched_filter, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-mf_f.dat"))
self.connect(self.normalize, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-theta_f.dat"))
self.connect(self.angle, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-epsilon_f.dat"))
self.connect(self.pk_detect, gr.file_sink(gr.sizeof_char, "ofdm_sync_pn-peaks_b.dat"))
self.connect(self.sample_and_hold, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-sample_and_hold_f.dat"))
self.connect(self.input, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_pn-input_c.dat"))
def __init__(self, fft_length, cp_length, half_sync, kstime, ks1time, threshold, logging=False):
gr.hier_block2.__init__(
self,
"ofdm_sync_pn",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature3(
3,
3, # Output signature
gr.sizeof_gr_complex, # delayed input
gr.sizeof_float, # fine frequency offset
gr.sizeof_char, # timing indicator
),
)
if half_sync:
period = fft_length / 2
window = fft_length / 2
else: # full symbol
period = fft_length + cp_length
window = fft_length # makes the plateau cp_length long
# Calculate the frequency offset from the correlation of the preamble
x_corr = gr.multiply_cc()
self.connect(self, gr.conjugate_cc(), (x_corr, 0))
self.connect(self, gr.delay(gr.sizeof_gr_complex, period), (x_corr, 1))
P_d = gr.moving_average_cc(window, 1.0)
self.connect(x_corr, P_d)
# offset by -1
phi = gr.sample_and_hold_ff()
self.corrmag = gr.complex_to_mag_squared()
P_d_angle = gr.complex_to_arg()
self.connect(P_d, P_d_angle, (phi, 0))
cross_correlate = 1
if cross_correlate == 1:
# cross-correlate with the known symbol
kstime = [k.conjugate() for k in kstime]
kstime.reverse()
self.crosscorr_filter = gr.fir_filter_ccc(1, kstime)
"""
self.f2b = gr.float_to_char()
self.slice = gr.threshold_ff(threshold, threshold, 0, fft_length)
#self.connect(self, self.crosscorr_filter, self.corrmag, self.slice, self.f2b)
self.connect(self.f2b, (phi,1))
self.connect(self.f2b, (self,2))
self.connect(self.f2b, gr.file_sink(gr.sizeof_char, "ofdm_f2b.dat"))
"""
# new method starts here - only crosscorrelate and use peak_detect block #
peak_detect = gr.peak_detector_fb(100, 100, 30, 0.001)
self.corrmag1 = gr.complex_to_mag_squared()
self.connect(self, self.crosscorr_filter, self.corrmag, peak_detect)
self.connect(peak_detect, (phi, 1))
self.connect(peak_detect, (self, 2))
self.connect(peak_detect, gr.file_sink(gr.sizeof_char, "sync-peaks_b.dat"))
self.connect(self.corrmag, gr.file_sink(gr.sizeof_float, "ofdm_corrmag.dat"))
self.connect(self, gr.delay(gr.sizeof_gr_complex, (fft_length)), (self, 0))
else:
# Get the power of the input signal to normalize the output of the correlation
R_d = gr.moving_average_ff(window, 1.0)
self.connect(self, gr.complex_to_mag_squared(), R_d)
R_d_squared = gr.multiply_ff() # this is retarded
self.connect(R_d, (R_d_squared, 0))
self.connect(R_d, (R_d_squared, 1))
M_d = gr.divide_ff()
self.connect(P_d, gr.complex_to_mag_squared(), (M_d, 0))
self.connect(R_d_squared, (M_d, 1))
# Now we need to detect peak of M_d
matched_filter = gr.moving_average_ff(cp_length, 1.0 / cp_length)
peak_detect = gr.peak_detector_fb(0.25, 0.25, 30, 0.001)
self.connect(M_d, matched_filter, gr.add_const_ff(-1), peak_detect)
offset = cp_length / 2 # cp_length/2
self.connect(peak_detect, (phi, 1))
self.connect(peak_detect, (self, 2))
self.connect(P_d_angle, gr.delay(gr.sizeof_float, offset), (phi, 0))
self.connect(
self, gr.delay(gr.sizeof_gr_complex, (fft_length + offset)), (self, 0)
) # delay the input to follow the freq offset
self.connect(peak_detect, gr.delay(gr.sizeof_char, (fft_length + offset)), (self, 2))
self.connect(peak_detect, gr.file_sink(gr.sizeof_char, "sync-peaks_b.dat"))
self.connect(matched_filter, gr.file_sink(gr.sizeof_float, "sync-mf.dat"))
self.connect(phi, (self, 1))
if logging:
self.connect(matched_filter, gr.file_sink(gr.sizeof_float, "sync-mf.dat"))
self.connect(M_d, gr.file_sink(gr.sizeof_float, "sync-M.dat"))
self.connect(P_d_angle, gr.file_sink(gr.sizeof_float, "sync-angle.dat"))
self.connect(peak_detect, gr.file_sink(gr.sizeof_char, "sync-peaks.datb"))
self.connect(phi, gr.file_sink(gr.sizeof_float, "sync-phi.dat"))
def __init__(self, subc, vlen, ss):
gr.hier_block2.__init__(
self,
"new_snr_estimator",
gr.io_signature(2, 2, gr.sizeof_gr_complex * vlen),
#gr.io_signature2(2,2,gr.sizeof_float*vlen,gr.sizeof_float*vlen/ss*(ss-1)))
gr.io_signature2(2, 2, gr.sizeof_float * vlen, gr.sizeof_float))
print "Created Milan's SINR estimator"
trigger = [0] * vlen
trigger[0] = 1
v = range(vlen / ss)
ones_ind = map(lambda z: z * ss, v)
skip2_pr0 = skip(gr.sizeof_gr_complex, vlen)
skip2_pr1 = skip(gr.sizeof_gr_complex, vlen)
for x in ones_ind:
skip2_pr0.skip(x)
skip2_pr1.skip(x)
#print "skipped ones",ones_ind
v2s_pr0 = gr.vector_to_stream(gr.sizeof_gr_complex, vlen)
v2s_pr1 = gr.vector_to_stream(gr.sizeof_gr_complex, vlen)
s2v2_pr0 = gr.stream_to_vector(gr.sizeof_gr_complex,
vlen / ss * (ss - 1))
trigger_src_2_pr0 = gr.vector_source_b(trigger, True)
s2v2_pr1 = gr.stream_to_vector(gr.sizeof_gr_complex,
vlen / ss * (ss - 1))
trigger_src_2_pr1 = gr.vector_source_b(trigger, True)
mag_sq_zeros_pr0 = gr.complex_to_mag_squared(vlen / ss * (ss - 1))
mag_sq_zeros_pr1 = gr.complex_to_mag_squared(vlen / ss * (ss - 1))
filt_zeros_pr0 = gr.single_pole_iir_filter_ff(0.01,
vlen / ss * (ss - 1))
filt_zeros_pr1 = gr.single_pole_iir_filter_ff(0.01,
vlen / ss * (ss - 1))
v1 = vlen / ss * (ss - 1)
vevc1 = [-1] * v1
neg_nomin_z = gr.multiply_const_vff(vevc1)
div_z = gr.divide_ff(vlen / ss * (ss - 1))
on_zeros = gr.add_const_vff(vevc1)
sum_zeros = add_vff(vlen / ss * (ss - 1))
# For average
sum_all = vector_sum_vff(vlen)
mult = gr.multiply_const_ff(1. / vlen)
scsnr_db_av = gr.nlog10_ff(10, 1, 0)
filt_end_av = gr.single_pole_iir_filter_ff(0.1)
self.connect((self, 0), v2s_pr0, skip2_pr0, s2v2_pr0, mag_sq_zeros_pr0,
filt_zeros_pr0)
self.connect(trigger_src_2_pr0, (skip2_pr0, 1))
self.connect((self, 1), v2s_pr1, skip2_pr1, s2v2_pr1, mag_sq_zeros_pr1,
filt_zeros_pr1)
self.connect(trigger_src_2_pr1, (skip2_pr1, 1))
# On zeros
self.connect(filt_zeros_pr1, (sum_zeros, 0))
self.connect(filt_zeros_pr0, neg_nomin_z, (sum_zeros, 1))
self.connect(sum_zeros, div_z)
self.connect(filt_zeros_pr0, (div_z, 1))
scsnr_db = gr.nlog10_ff(10, vlen, 0)
filt_end = gr.single_pole_iir_filter_ff(0.1, vlen)
dd = []
for i in range(vlen / ss):
dd.extend([i * ss])
#print dd
interpolator = sinr_interpolator(vlen, ss, dd)
self.connect(div_z, interpolator, filt_end, scsnr_db, self)
self.connect(interpolator, sum_all, mult, scsnr_db_av, filt_end_av,
(self, 1))
def __init__(self, fft_length, cp_length, snr, kstime, logging):
''' Maximum Likelihood OFDM synchronizer:
J. van de Beek, M. Sandell, and P. O. Borjesson, "ML Estimation
of Time and Frequency Offset in OFDM Systems," IEEE Trans.
Signal Processing, vol. 45, no. 7, pp. 1800-1805, 1997.
'''
gr.hier_block2.__init__(self, "ofdm_sync_ml",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
SNR = 10.0**(snr/10.0)
rho = SNR / (SNR + 1.0)
symbol_length = fft_length + cp_length
# ML Sync
# Energy Detection from ML Sync
self.connect(self, self.input)
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length)
self.connect(self.input, self.delay)
# magnitude squared blocks
self.magsqrd1 = gr.complex_to_mag_squared()
self.magsqrd2 = gr.complex_to_mag_squared()
self.adder = gr.add_ff()
moving_sum_taps = [rho/2 for i in range(cp_length)]
self.moving_sum_filter = gr.fir_filter_fff(1,moving_sum_taps)
self.connect(self.input,self.magsqrd1)
self.connect(self.delay,self.magsqrd2)
self.connect(self.magsqrd1,(self.adder,0))
self.connect(self.magsqrd2,(self.adder,1))
self.connect(self.adder,self.moving_sum_filter)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc();
self.mixer = gr.multiply_cc();
movingsum2_taps = [1.0 for i in range(cp_length)]
self.movingsum2 = gr.fir_filter_ccf(1,movingsum2_taps)
# Correlator data handler
self.c2mag = gr.complex_to_mag()
self.angle = gr.complex_to_arg()
self.connect(self.input,(self.mixer,1))
self.connect(self.delay,self.conjg,(self.mixer,0))
self.connect(self.mixer,self.movingsum2,self.c2mag)
self.connect(self.movingsum2,self.angle)
# ML Sync output arg, need to find maximum point of this
self.diff = gr.sub_ff()
self.connect(self.c2mag,(self.diff,0))
self.connect(self.moving_sum_filter,(self.diff,1))
#ML measurements input to sampler block and detect
self.f2c = gr.float_to_complex()
self.pk_detect = gr.peak_detector_fb(0.2, 0.25, 30, 0.0005)
self.sample_and_hold = gr.sample_and_hold_ff()
# use the sync loop values to set the sampler and the NCO
# self.diff = theta
# self.angle = epsilon
self.connect(self.diff, self.pk_detect)
# The DPLL corrects for timing differences between CP correlations
use_dpll = 0
if use_dpll:
self.dpll = gr.dpll_bb(float(symbol_length),0.01)
self.connect(self.pk_detect, self.dpll)
self.connect(self.dpll, (self.sample_and_hold,1))
else:
self.connect(self.pk_detect, (self.sample_and_hold,1))
self.connect(self.angle, (self.sample_and_hold,0))
################################
# correlate against known symbol
# This gives us the same timing signal as the PN sync block only on the preamble
# we don't use the signal generated from the CP correlation because we don't want
# to readjust the timing in the middle of the packet or we ruin the equalizer settings.
kstime = [k.conjugate() for k in kstime]
kstime.reverse()
self.kscorr = gr.fir_filter_ccc(1, kstime)
self.corrmag = gr.complex_to_mag_squared()
self.div = gr.divide_ff()
# The output signature of the correlation has a few spikes because the rest of the
# system uses the repeated preamble symbol. It needs to work that generically if
# anyone wants to use this against a WiMAX-like signal since it, too, repeats.
# The output theta of the correlator above is multiplied with this correlation to
# identify the proper peak and remove other products in this cross-correlation
self.threshold_factor = 0.1
self.slice = gr.threshold_ff(self.threshold_factor, self.threshold_factor, 0)
self.f2b = gr.float_to_char()
self.b2f = gr.char_to_float()
self.mul = gr.multiply_ff()
# Normalize the power of the corr output by the energy. This is not really needed
# and could be removed for performance, but it makes for a cleaner signal.
# if this is removed, the threshold value needs adjustment.
self.connect(self.input, self.kscorr, self.corrmag, (self.div,0))
self.connect(self.moving_sum_filter, (self.div,1))
self.connect(self.div, (self.mul,0))
self.connect(self.pk_detect, self.b2f, (self.mul,1))
self.connect(self.mul, self.slice)
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self,0))
self.connect(self.slice, self.f2b, (self,1))
if logging:
self.connect(self.moving_sum_filter, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-energy_f.dat"))
self.connect(self.diff, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-theta_f.dat"))
self.connect(self.angle, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-epsilon_f.dat"))
self.connect(self.corrmag, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-corrmag_f.dat"))
self.connect(self.kscorr, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_ml-kscorr_c.dat"))
self.connect(self.div, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-div_f.dat"))
self.connect(self.mul, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-mul_f.dat"))
self.connect(self.slice, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-slice_f.dat"))
self.connect(self.pk_detect, gr.file_sink(gr.sizeof_char, "ofdm_sync_ml-peaks_b.dat"))
if use_dpll:
self.connect(self.dpll, gr.file_sink(gr.sizeof_char, "ofdm_sync_ml-dpll_b.dat"))
self.connect(self.sample_and_hold, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-sample_and_hold_f.dat"))
self.connect(self.input, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_ml-input_c.dat"))
def __init__(self, devid="type=b100", rdsfile="rds_fifo", gain=35.0, freq=101.1e6, xmlport=13777, arate=int(48e3), mute=-15.0, ftune=0, ant="J1", subdev="A:0", ahw="pulse", deemph=75.0e-6, prenames='["UWRF","89.3","950","WEVR"]', prefreqs="[88.715e6,89.3e6,950.735e6,106.317e6]", volume=1.0):
grc_wxgui.top_block_gui.__init__(self, title="Simple FM (Stereo) Receiver")
_icon_path = "/usr/share/icons/hicolor/32x32/apps/gnuradio-grc.png"
self.SetIcon(wx.Icon(_icon_path, wx.BITMAP_TYPE_ANY))
##################################################
# Parameters
##################################################
self.devid = devid
self.rdsfile = rdsfile
self.gain = gain
self.freq = freq
self.xmlport = xmlport
self.arate = arate
self.mute = mute
self.ftune = ftune
self.ant = ant
self.subdev = subdev
self.ahw = ahw
self.deemph = deemph
self.prenames = prenames
self.prefreqs = prefreqs
self.volume = volume
##################################################
# Variables
##################################################
self.pthresh = pthresh = 350
self.preselect = preselect = eval(prefreqs)[0]
self.pilot_level = pilot_level = 0
self.ifreq = ifreq = freq
self.stpilotdet = stpilotdet = True if (pilot_level > pthresh) else False
self.stereo = stereo = True
self.rf_pwr_lvl = rf_pwr_lvl = 0
self.cur_freq = cur_freq = simple_fm_helper.freq_select(ifreq,preselect)
self.vol = vol = volume
self.variable_static_text_0 = variable_static_text_0 = 10.0*math.log(rf_pwr_lvl+1.0e-11)/math.log(10)
self.tone_med = tone_med = 5
self.tone_low = tone_low = 5
self.tone_high = tone_high = 5
self.stereo_0 = stereo_0 = stpilotdet
self.st_enabled = st_enabled = 1 if (stereo == True and pilot_level > pthresh) else 0
self.squelch_probe = squelch_probe = 0
self.sq_thresh = sq_thresh = mute
self.samp_rate = samp_rate = 250e3
self.rtext_0 = rtext_0 = cur_freq
self.record = record = False
self.rdsrate = rdsrate = 25e3
self.osmo_taps = osmo_taps = firdes.low_pass(1.0,1.00e6,95e3,20e3,firdes.WIN_HAMMING,6.76)
self.mod_reset = mod_reset = 0
self.igain = igain = gain
self.fine = fine = ftune
self.farate = farate = arate
self.dm = dm = deemph
self.discrim_dc = discrim_dc = 0
self.capture_file = capture_file = "capture.wav"
self.asrate = asrate = 125e3
##################################################
# Blocks
##################################################
_sq_thresh_sizer = wx.BoxSizer(wx.VERTICAL)
self._sq_thresh_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_sq_thresh_sizer,
value=self.sq_thresh,
callback=self.set_sq_thresh,
label="Mute Level",
converter=forms.float_converter(),
proportion=0,
)
self._sq_thresh_slider = forms.slider(
parent=self.GetWin(),
sizer=_sq_thresh_sizer,
value=self.sq_thresh,
callback=self.set_sq_thresh,
minimum=-30.0,
maximum=-5.0,
num_steps=40,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.GridAdd(_sq_thresh_sizer, 1, 5, 1, 1)
self.input_power = gr.probe_avg_mag_sqrd_c(sq_thresh, 1.0/(samp_rate/10))
self.dc_level = gr.probe_signal_f()
_vol_sizer = wx.BoxSizer(wx.VERTICAL)
self._vol_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_vol_sizer,
value=self.vol,
callback=self.set_vol,
label="Volume",
converter=forms.float_converter(),
proportion=0,
)
self._vol_slider = forms.slider(
parent=self.GetWin(),
sizer=_vol_sizer,
value=self.vol,
callback=self.set_vol,
minimum=0,
maximum=11,
num_steps=110,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.GridAdd(_vol_sizer, 0, 3, 1, 1)
_tone_med_sizer = wx.BoxSizer(wx.VERTICAL)
self._tone_med_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_tone_med_sizer,
value=self.tone_med,
callback=self.set_tone_med,
label="1Khz-4Khz",
converter=forms.float_converter(),
proportion=0,
)
self._tone_med_slider = forms.slider(
parent=self.GetWin(),
sizer=_tone_med_sizer,
value=self.tone_med,
callback=self.set_tone_med,
minimum=0,
maximum=10,
num_steps=100,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.GridAdd(_tone_med_sizer, 1, 3, 1, 1)
_tone_low_sizer = wx.BoxSizer(wx.VERTICAL)
self._tone_low_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_tone_low_sizer,
value=self.tone_low,
callback=self.set_tone_low,
label="0-1Khz",
converter=forms.float_converter(),
proportion=0,
)
self._tone_low_slider = forms.slider(
parent=self.GetWin(),
sizer=_tone_low_sizer,
value=self.tone_low,
callback=self.set_tone_low,
minimum=0,
maximum=10,
num_steps=100,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.GridAdd(_tone_low_sizer, 1, 2, 1, 1)
_tone_high_sizer = wx.BoxSizer(wx.VERTICAL)
self._tone_high_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_tone_high_sizer,
value=self.tone_high,
callback=self.set_tone_high,
label="4Khz-15Khz",
converter=forms.float_converter(),
proportion=0,
)
self._tone_high_slider = forms.slider(
parent=self.GetWin(),
sizer=_tone_high_sizer,
value=self.tone_high,
callback=self.set_tone_high,
minimum=0,
maximum=10,
num_steps=100,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.GridAdd(_tone_high_sizer, 1, 4, 1, 1)
def _squelch_probe_probe():
while True:
val = self.input_power.unmuted()
try: self.set_squelch_probe(val)
except AttributeError, e: pass
time.sleep(1.0/(10))
_squelch_probe_thread = threading.Thread(target=_squelch_probe_probe)
_squelch_probe_thread.daemon = True
_squelch_probe_thread.start()
self._record_check_box = forms.check_box(
parent=self.GetWin(),
value=self.record,
callback=self.set_record,
label="Record Audio",
true=True,
false=False,
)
self.GridAdd(self._record_check_box, 2, 2, 1, 1)
self.pilot_probe = gr.probe_signal_f()
_fine_sizer = wx.BoxSizer(wx.VERTICAL)
self._fine_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_fine_sizer,
value=self.fine,
callback=self.set_fine,
label="Fine Tuning",
converter=forms.float_converter(),
proportion=0,
)
self._fine_slider = forms.slider(
parent=self.GetWin(),
sizer=_fine_sizer,
value=self.fine,
callback=self.set_fine,
minimum=-50.0e3,
maximum=50.e03,
num_steps=400,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.GridAdd(_fine_sizer, 1, 0, 1, 1)
def _discrim_dc_probe():
while True:
val = self.dc_level.level()
try: self.set_discrim_dc(val)
except AttributeError, e: pass
time.sleep(1.0/(2.5))
_discrim_dc_thread = threading.Thread(target=_discrim_dc_probe)
_discrim_dc_thread.daemon = True
_discrim_dc_thread.start()
self._capture_file_text_box = forms.text_box(
parent=self.GetWin(),
value=self.capture_file,
callback=self.set_capture_file,
label="Record Filename",
converter=forms.str_converter(),
)
self.GridAdd(self._capture_file_text_box, 2, 0, 1, 2)
self.Main = self.Main = wx.Notebook(self.GetWin(), style=wx.NB_TOP)
self.Main.AddPage(grc_wxgui.Panel(self.Main), "L/R")
self.Main.AddPage(grc_wxgui.Panel(self.Main), "FM Demod Spectrum")
self.Add(self.Main)
self.wxgui_waterfallsink2_0 = waterfallsink2.waterfall_sink_c(
self.GetWin(),
baseband_freq=0,
dynamic_range=100,
ref_level=0,
ref_scale=2.0,
sample_rate=samp_rate,
fft_size=512,
fft_rate=15,
average=False,
avg_alpha=None,
title="Waterfall Plot",
)
self.Add(self.wxgui_waterfallsink2_0.win)
self.wxgui_scopesink2_0 = scopesink2.scope_sink_f(
self.Main.GetPage(0).GetWin(),
title="Audio Channels (L and R)",
sample_rate=farate,
v_scale=0,
v_offset=0,
t_scale=0,
ac_couple=False,
xy_mode=False,
num_inputs=2,
trig_mode=gr.gr_TRIG_MODE_AUTO,
y_axis_label="Rel. Audio Level",
)
self.Main.GetPage(0).Add(self.wxgui_scopesink2_0.win)
self.wxgui_fftsink2_0 = fftsink2.fft_sink_f(
self.Main.GetPage(1).GetWin(),
baseband_freq=0,
y_per_div=10,
y_divs=10,
ref_level=0,
ref_scale=2.0,
sample_rate=asrate,
fft_size=1024,
fft_rate=6,
average=True,
avg_alpha=0.1,
title="FM Demod Spectrum",
peak_hold=False,
)
self.Main.GetPage(1).Add(self.wxgui_fftsink2_0.win)
self._variable_static_text_0_static_text = forms.static_text(
parent=self.GetWin(),
value=self.variable_static_text_0,
callback=self.set_variable_static_text_0,
label="RF Power ",
converter=forms.float_converter(formatter=lambda x: "%4.1f" % x),
)
self.GridAdd(self._variable_static_text_0_static_text, 0, 2, 1, 1)
self._stereo_0_check_box = forms.check_box(
parent=self.GetWin(),
value=self.stereo_0,
callback=self.set_stereo_0,
label="Stereo Detect",
true=True,
false=False,
)
self.GridAdd(self._stereo_0_check_box, 2, 5, 1, 1)
self._stereo_check_box = forms.check_box(
parent=self.GetWin(),
value=self.stereo,
callback=self.set_stereo,
label="Stereo",
true=True,
false=False,
)
self.GridAdd(self._stereo_check_box, 2, 4, 1, 1)
self.rtl2832_source_0 = baz.rtl_source_c(defer_creation=True)
self.rtl2832_source_0.set_verbose(True)
self.rtl2832_source_0.set_vid(0x0)
self.rtl2832_source_0.set_pid(0x0)
self.rtl2832_source_0.set_tuner_name("")
self.rtl2832_source_0.set_default_timeout(0)
self.rtl2832_source_0.set_use_buffer(True)
self.rtl2832_source_0.set_fir_coefficients(([]))
if self.rtl2832_source_0.create() == False: raise Exception("Failed to create RTL2832 Source: rtl2832_source_0")
self.rtl2832_source_0.set_sample_rate(1.0e6)
self.rtl2832_source_0.set_frequency(cur_freq+200e3)
self.rtl2832_source_0.set_auto_gain_mode(False)
self.rtl2832_source_0.set_relative_gain(True)
self.rtl2832_source_0.set_gain(gain)
self._rtext_0_static_text = forms.static_text(
parent=self.GetWin(),
value=self.rtext_0,
callback=self.set_rtext_0,
label="CURRENT FREQUENCY>>",
converter=forms.float_converter(),
)
self.GridAdd(self._rtext_0_static_text, 0, 1, 1, 1)
def _rf_pwr_lvl_probe():
while True:
val = self.input_power.level()
try: self.set_rf_pwr_lvl(val)
except AttributeError, e: pass
time.sleep(1.0/(2))
_rf_pwr_lvl_thread = threading.Thread(target=_rf_pwr_lvl_probe)
_rf_pwr_lvl_thread.daemon = True
_rf_pwr_lvl_thread.start()
self._preselect_chooser = forms.radio_buttons(
parent=self.GetWin(),
value=self.preselect,
callback=self.set_preselect,
label='preselect',
choices=eval(prefreqs),
labels=eval(prenames),
style=wx.RA_HORIZONTAL,
)
self.GridAdd(self._preselect_chooser, 0, 4, 1, 1)
def _pilot_level_probe():
while True:
val = self.pilot_probe.level()
try: self.set_pilot_level(val)
except AttributeError, e: pass
time.sleep(1.0/(5))
_pilot_level_thread = threading.Thread(target=_pilot_level_probe)
_pilot_level_thread.daemon = True
_pilot_level_thread.start()
self.low_pass_filter_3 = gr.fir_filter_fff(1, firdes.low_pass(
3, asrate/500, 10, 3, firdes.WIN_HAMMING, 6.76))
self.low_pass_filter_2 = gr.fir_filter_fff(10, firdes.low_pass(
3, asrate/50, 100, 30, firdes.WIN_HAMMING, 6.76))
self.low_pass_filter_1 = gr.fir_filter_fff(10, firdes.low_pass(
3, asrate/5, 1e3, 200, firdes.WIN_HAMMING, 6.76))
self.low_pass_filter_0 = gr.fir_filter_fff(5, firdes.low_pass(
3, asrate, 10e3, 2e3, firdes.WIN_HAMMING, 6.76))
_igain_sizer = wx.BoxSizer(wx.VERTICAL)
self._igain_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_igain_sizer,
value=self.igain,
callback=self.set_igain,
label="RF Gain",
converter=forms.float_converter(),
proportion=0,
)
self._igain_slider = forms.slider(
parent=self.GetWin(),
sizer=_igain_sizer,
value=self.igain,
callback=self.set_igain,
minimum=0,
maximum=50,
num_steps=100,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.GridAdd(_igain_sizer, 1, 1, 1, 1)
_ifreq_sizer = wx.BoxSizer(wx.VERTICAL)
self._ifreq_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_ifreq_sizer,
value=self.ifreq,
callback=self.set_ifreq,
label="Center Frequency",
converter=forms.float_converter(),
proportion=0,
)
self._ifreq_slider = forms.slider(
parent=self.GetWin(),
sizer=_ifreq_sizer,
value=self.ifreq,
callback=self.set_ifreq,
minimum=88.1e6,
maximum=108.1e6,
num_steps=200,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.GridAdd(_ifreq_sizer, 0, 0, 1, 1)
self.gr_wavfile_sink_0 = gr.wavfile_sink("/dev/null" if record == False else capture_file, 2, int(farate), 16)
self.gr_sub_xx_0 = gr.sub_ff(1)
self.gr_single_pole_iir_filter_xx_1 = gr.single_pole_iir_filter_ff(2.5/(asrate/500), 1)
self.gr_single_pole_iir_filter_xx_0 = gr.single_pole_iir_filter_ff(1.0/(asrate/3), 1)
self.gr_multiply_xx_1 = gr.multiply_vff(1)
self.gr_multiply_xx_0_0 = gr.multiply_vff(1)
self.gr_multiply_xx_0 = gr.multiply_vff(1)
self.gr_multiply_const_vxx_3 = gr.multiply_const_vff((3.16e3 if st_enabled else 0, ))
self.gr_multiply_const_vxx_2 = gr.multiply_const_vff((1.0 if st_enabled else 1.414, ))
self.gr_multiply_const_vxx_1_0 = gr.multiply_const_vff((0 if st_enabled else 1, ))
self.gr_multiply_const_vxx_1 = gr.multiply_const_vff((0 if squelch_probe == 0 else 1.0, ))
self.gr_multiply_const_vxx_0_0 = gr.multiply_const_vff((vol*1.5*10.0, ))
self.gr_multiply_const_vxx_0 = gr.multiply_const_vff((vol*1.5*10.0 if st_enabled else 0, ))
self.gr_keep_one_in_n_0 = gr.keep_one_in_n(gr.sizeof_float*1, int(asrate/3))
self.gr_freq_xlating_fir_filter_xxx_0 = gr.freq_xlating_fir_filter_ccc(4, (osmo_taps), 200e3+fine+(-12e3*discrim_dc), 1.0e6)
self.gr_fractional_interpolator_xx_0_0 = gr.fractional_interpolator_ff(0, asrate/farate)
self.gr_fractional_interpolator_xx_0 = gr.fractional_interpolator_ff(0, asrate/farate)
self.gr_fft_filter_xxx_1_0_0 = gr.fft_filter_fff(1, (firdes.band_pass(tone_high/10.0,asrate,3.5e3,15.0e3,5.0e3,firdes.WIN_HAMMING)), 1)
self.gr_fft_filter_xxx_1_0 = gr.fft_filter_fff(1, (firdes.band_pass(tone_med/10.0,asrate,1.0e3,4.0e3,2.0e3,firdes.WIN_HAMMING)), 1)
self.gr_fft_filter_xxx_1 = gr.fft_filter_fff(1, (firdes.low_pass(tone_low/10.0,asrate,1.2e3,500,firdes.WIN_HAMMING)), 1)
self.gr_fft_filter_xxx_0_0_0 = gr.fft_filter_fff(1, (firdes.band_pass(tone_high/10.0,asrate,3.5e3,13.5e3,3.5e3,firdes.WIN_HAMMING)), 1)
self.gr_fft_filter_xxx_0_0 = gr.fft_filter_fff(1, (firdes.band_pass(tone_med/10.0,asrate,1.0e3,4.0e3,2.0e3,firdes.WIN_HAMMING)), 1)
self.gr_fft_filter_xxx_0 = gr.fft_filter_fff(1, (firdes.low_pass(tone_low/10.0,asrate,1.2e3,500,firdes.WIN_HAMMING)), 1)
self.gr_divide_xx_0 = gr.divide_ff(1)
self.gr_agc_xx_1 = gr.agc_cc(1e-2, 0.35, 1.0, 5000)
self.gr_add_xx_2_0 = gr.add_vff(1)
self.gr_add_xx_2 = gr.add_vff(1)
self.gr_add_xx_1 = gr.add_vff(1)
self.gr_add_xx_0 = gr.add_vff(1)
self.gr_add_const_vxx_0 = gr.add_const_vff((1.0e-7, ))
self._dm_chooser = forms.radio_buttons(
parent=self.GetWin(),
value=self.dm,
callback=self.set_dm,
label="FM Deemphasis",
choices=[75.0e-6, 50.0e-6],
labels=["NA", "EU"],
style=wx.RA_HORIZONTAL,
)
self.GridAdd(self._dm_chooser, 0, 5, 1, 1)
self.blks2_wfm_rcv_0 = blks2.wfm_rcv(
quad_rate=samp_rate,
audio_decimation=2,
)
self.blks2_fm_deemph_0_0 = blks2.fm_deemph(fs=farate, tau=deemph)
self.blks2_fm_deemph_0 = blks2.fm_deemph(fs=farate, tau=deemph)
self.band_pass_filter_2_0 = gr.fir_filter_fff(1, firdes.band_pass(
20, asrate, 17.5e3, 17.9e3, 250, firdes.WIN_HAMMING, 6.76))
self.band_pass_filter_2 = gr.fir_filter_fff(1, firdes.band_pass(
10, asrate, 18.8e3, 19.2e3, 350, firdes.WIN_HAMMING, 6.76))
self.band_pass_filter_0_0 = gr.fir_filter_fff(1, firdes.band_pass(
1, asrate, 38e3-(15e3), 38e3+(15e3), 4.0e3, firdes.WIN_HAMMING, 6.76))
self.audio_sink_0 = audio.sink(int(farate), "" if ahw == "Default" else ahw, True)
##################################################
# Connections
##################################################
self.connect((self.gr_add_xx_1, 0), (self.gr_fractional_interpolator_xx_0, 0))
self.connect((self.gr_sub_xx_0, 0), (self.gr_fractional_interpolator_xx_0_0, 0))
self.connect((self.band_pass_filter_0_0, 0), (self.gr_multiply_xx_1, 0))
self.connect((self.gr_multiply_const_vxx_1_0, 0), (self.gr_add_xx_0, 0))
self.connect((self.band_pass_filter_2_0, 0), (self.gr_multiply_xx_0, 0))
self.connect((self.band_pass_filter_2_0, 0), (self.gr_multiply_xx_0, 1))
self.connect((self.gr_multiply_xx_0_0, 0), (self.gr_divide_xx_0, 0))
self.connect((self.gr_divide_xx_0, 0), (self.gr_single_pole_iir_filter_xx_0, 0))
self.connect((self.gr_multiply_xx_0, 0), (self.gr_add_const_vxx_0, 0))
self.connect((self.gr_add_const_vxx_0, 0), (self.gr_divide_xx_0, 1))
self.connect((self.gr_single_pole_iir_filter_xx_0, 0), (self.gr_keep_one_in_n_0, 0))
self.connect((self.gr_keep_one_in_n_0, 0), (self.pilot_probe, 0))
self.connect((self.band_pass_filter_2, 0), (self.gr_multiply_xx_1, 2))
self.connect((self.band_pass_filter_2, 0), (self.gr_multiply_xx_0_0, 0))
self.connect((self.gr_multiply_const_vxx_2, 0), (self.gr_add_xx_1, 0))
self.connect((self.gr_multiply_const_vxx_2, 0), (self.gr_sub_xx_0, 0))
self.connect((self.gr_multiply_const_vxx_3, 0), (self.gr_sub_xx_0, 1))
self.connect((self.gr_multiply_const_vxx_3, 0), (self.gr_add_xx_1, 1))
self.connect((self.gr_fractional_interpolator_xx_0, 0), (self.gr_multiply_const_vxx_0_0, 0))
self.connect((self.gr_fractional_interpolator_xx_0_0, 0), (self.gr_multiply_const_vxx_0, 0))
self.connect((self.band_pass_filter_2, 0), (self.gr_multiply_xx_1, 1))
self.connect((self.gr_multiply_xx_1, 0), (self.gr_fft_filter_xxx_0, 0))
self.connect((self.gr_fft_filter_xxx_1, 0), (self.gr_add_xx_2, 0))
self.connect((self.gr_fft_filter_xxx_1_0, 0), (self.gr_add_xx_2, 1))
self.connect((self.gr_fft_filter_xxx_1_0_0, 0), (self.gr_add_xx_2, 2))
self.connect((self.gr_add_xx_2, 0), (self.gr_multiply_const_vxx_2, 0))
self.connect((self.gr_add_xx_2_0, 0), (self.gr_multiply_const_vxx_3, 0))
self.connect((self.gr_fft_filter_xxx_0, 0), (self.gr_add_xx_2_0, 0))
self.connect((self.gr_fft_filter_xxx_0_0, 0), (self.gr_add_xx_2_0, 1))
self.connect((self.gr_multiply_xx_1, 0), (self.gr_fft_filter_xxx_0_0, 0))
self.connect((self.gr_fft_filter_xxx_0_0_0, 0), (self.gr_add_xx_2_0, 2))
self.connect((self.gr_multiply_xx_1, 0), (self.gr_fft_filter_xxx_0_0_0, 0))
self.connect((self.blks2_fm_deemph_0, 0), (self.gr_multiply_const_vxx_1_0, 0))
self.connect((self.blks2_fm_deemph_0, 0), (self.gr_wavfile_sink_0, 0))
self.connect((self.gr_multiply_const_vxx_1, 0), (self.gr_fft_filter_xxx_1, 0))
self.connect((self.gr_multiply_const_vxx_1, 0), (self.gr_fft_filter_xxx_1_0, 0))
self.connect((self.gr_multiply_const_vxx_1, 0), (self.gr_fft_filter_xxx_1_0_0, 0))
self.connect((self.gr_multiply_const_vxx_1, 0), (self.wxgui_fftsink2_0, 0))
self.connect((self.gr_multiply_const_vxx_0_0, 0), (self.blks2_fm_deemph_0, 0))
self.connect((self.gr_add_xx_0, 0), (self.audio_sink_0, 1))
self.connect((self.gr_multiply_const_vxx_0, 0), (self.blks2_fm_deemph_0_0, 0))
self.connect((self.blks2_fm_deemph_0_0, 0), (self.gr_add_xx_0, 1))
self.connect((self.band_pass_filter_2, 0), (self.gr_multiply_xx_0_0, 1))
self.connect((self.gr_multiply_const_vxx_1, 0), (self.band_pass_filter_2, 0))
self.connect((self.blks2_fm_deemph_0, 0), (self.audio_sink_0, 0))
self.connect((self.gr_multiply_const_vxx_1, 0), (self.band_pass_filter_2_0, 0))
self.connect((self.gr_multiply_const_vxx_1, 0), (self.band_pass_filter_0_0, 0))
self.connect((self.gr_add_xx_0, 0), (self.gr_wavfile_sink_0, 1))
self.connect((self.blks2_fm_deemph_0, 0), (self.wxgui_scopesink2_0, 0))
self.connect((self.gr_add_xx_0, 0), (self.wxgui_scopesink2_0, 1))
self.connect((self.blks2_wfm_rcv_0, 0), (self.gr_multiply_const_vxx_1, 0))
self.connect((self.gr_agc_xx_1, 0), (self.blks2_wfm_rcv_0, 0))
self.connect((self.gr_freq_xlating_fir_filter_xxx_0, 0), (self.gr_agc_xx_1, 0))
self.connect((self.gr_freq_xlating_fir_filter_xxx_0, 0), (self.input_power, 0))
self.connect((self.blks2_wfm_rcv_0, 0), (self.low_pass_filter_0, 0))
self.connect((self.low_pass_filter_0, 0), (self.low_pass_filter_1, 0))
self.connect((self.low_pass_filter_1, 0), (self.low_pass_filter_2, 0))
self.connect((self.low_pass_filter_2, 0), (self.low_pass_filter_3, 0))
self.connect((self.gr_single_pole_iir_filter_xx_1, 0), (self.dc_level, 0))
self.connect((self.low_pass_filter_3, 0), (self.gr_single_pole_iir_filter_xx_1, 0))
self.connect((self.rtl2832_source_0, 0), (self.gr_freq_xlating_fir_filter_xxx_0, 0))
self.connect((self.gr_freq_xlating_fir_filter_xxx_0, 0), (self.wxgui_waterfallsink2_0, 0))
def __init__(self, subc, vlen, ss):
gr.hier_block2.__init__(self, "new_snr_estimator",
gr.io_signature(2,2,gr.sizeof_gr_complex*vlen),
#gr.io_signature2(2,2,gr.sizeof_float*vlen,gr.sizeof_float*vlen/ss*(ss-1)))
gr.io_signature2(2,2,gr.sizeof_float*vlen,gr.sizeof_float))
print "Created Milan's SINR estimator"
trigger = [0]*vlen
trigger[0] = 1
v = range (vlen/ss)
ones_ind= map(lambda z: z*ss,v)
skip2_pr0 = skip(gr.sizeof_gr_complex,vlen)
skip2_pr1 = skip(gr.sizeof_gr_complex,vlen)
for x in ones_ind:
skip2_pr0.skip(x)
skip2_pr1.skip(x)
#print "skipped ones",ones_ind
v2s_pr0 = gr.vector_to_stream(gr.sizeof_gr_complex,vlen)
v2s_pr1 = gr.vector_to_stream(gr.sizeof_gr_complex,vlen)
s2v2_pr0 = gr.stream_to_vector(gr.sizeof_gr_complex,vlen/ss*(ss-1))
trigger_src_2_pr0 = gr.vector_source_b(trigger,True)
s2v2_pr1 = gr.stream_to_vector(gr.sizeof_gr_complex,vlen/ss*(ss-1))
trigger_src_2_pr1 = gr.vector_source_b(trigger,True)
mag_sq_zeros_pr0 = gr.complex_to_mag_squared(vlen/ss*(ss-1))
mag_sq_zeros_pr1 = gr.complex_to_mag_squared(vlen/ss*(ss-1))
filt_zeros_pr0 = gr.single_pole_iir_filter_ff(0.01,vlen/ss*(ss-1))
filt_zeros_pr1 = gr.single_pole_iir_filter_ff(0.01,vlen/ss*(ss-1))
v1 = vlen/ss*(ss-1)
vevc1 =[-1]*v1
neg_nomin_z = gr.multiply_const_vff(vevc1)
div_z=gr.divide_ff(vlen/ss*(ss-1))
on_zeros = gr.add_const_vff(vevc1)
sum_zeros = add_vff(vlen/ss*(ss-1))
# For average
sum_all = vector_sum_vff(vlen)
mult = gr.multiply_const_ff(1./vlen)
scsnr_db_av = gr.nlog10_ff(10,1,0)
filt_end_av = gr.single_pole_iir_filter_ff(0.1)
self.connect((self,0),v2s_pr0,skip2_pr0,s2v2_pr0,mag_sq_zeros_pr0,filt_zeros_pr0)
self.connect(trigger_src_2_pr0,(skip2_pr0,1))
self.connect((self,1),v2s_pr1,skip2_pr1,s2v2_pr1,mag_sq_zeros_pr1,filt_zeros_pr1)
self.connect(trigger_src_2_pr1,(skip2_pr1,1))
# On zeros
self.connect(filt_zeros_pr1,(sum_zeros,0))
self.connect(filt_zeros_pr0,neg_nomin_z,(sum_zeros,1))
self.connect(sum_zeros,div_z)
self.connect(filt_zeros_pr0,(div_z,1))
scsnr_db = gr.nlog10_ff(10,vlen,0)
filt_end = gr.single_pole_iir_filter_ff(0.1,vlen)
dd = []
for i in range (vlen/ss):
dd.extend([i*ss])
#print dd
interpolator = sinr_interpolator(vlen, ss,dd)
self.connect(div_z,interpolator,filt_end,scsnr_db,self)
self.connect(interpolator,sum_all,mult,scsnr_db_av,filt_end_av,(self,1))
def __init__(self, fft_length, cp_length, kstime, threshold, threshold_type, threshold_gap, logging=False):
"""
OFDM synchronization using PN Correlation:
T. M. Schmidl and D. C. Cox, "Robust Frequency and Timing
Synchonization for OFDM," IEEE Trans. Communications, vol. 45,
no. 12, 1997.
"""
gr.hier_block2.__init__(self, "ofdm_sync_pn",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
# PN Sync
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length/2)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc();
self.corr = gr.multiply_cc();
# Create a moving sum filter for the corr output
if 1:
moving_sum_taps = [1.0 for i in range(fft_length//2)]
self.moving_sum_filter = gr.fir_filter_ccf(1,moving_sum_taps)
else:
moving_sum_taps = [complex(1.0,0.0) for i in range(fft_length//2)]
self.moving_sum_filter = gr.fft_filter_ccc(1,moving_sum_taps)
# Create a moving sum filter for the input
self.inputmag2 = gr.complex_to_mag_squared()
movingsum2_taps = [1.0 for i in range(fft_length//2)]
#movingsum2_taps = [0.5 for i in range(fft_length*4)] #apurv - implementing Veljo's suggestion, when pause b/w packets
if 1:
self.inputmovingsum = gr.fir_filter_fff(1,movingsum2_taps)
else:
self.inputmovingsum = gr.fft_filter_fff(1,movingsum2_taps)
self.square = gr.multiply_ff()
self.normalize = gr.divide_ff()
# Get magnitude (peaks) and angle (phase/freq error)
self.c2mag = gr.complex_to_mag_squared()
self.angle = gr.complex_to_arg()
self.sample_and_hold = gr.sample_and_hold_ff()
#ML measurements input to sampler block and detect
self.sub1 = gr.add_const_ff(-1)
self.pk_detect = gr.peak_detector_fb(0.20, 0.20, 30, 0.001) #apurv - implementing Veljo's suggestion, when pause b/w packets
self.connect(self, self.input)
# Calculate the frequency offset from the correlation of the preamble
self.connect(self.input, self.delay)
self.connect(self.input, (self.corr,0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr,1))
self.connect(self.corr, self.moving_sum_filter)
#self.connect(self.moving_sum_filter, self.c2mag)
self.connect(self.moving_sum_filter, self.angle)
self.connect(self.angle, (self.sample_and_hold,0)) # apurv--
#self.connect(self.angle, gr.delay(gr.sizeof_float, offset), (self.sample_and_hold, 0)) #apurv++
cross_correlate = 1
if cross_correlate==1:
# cross-correlate with the known symbol
kstime = [k.conjugate() for k in kstime]
kstime.reverse()
self.crosscorr_filter = gr.fir_filter_ccc(1, kstime)
# get the magnitude #
self.corrmag = gr.complex_to_mag_squared()
self.f2b = gr.float_to_char()
self.threshold_factor = threshold #0.0012 #0.012 #0.0015
if 0:
self.slice = gr.threshold_ff(self.threshold_factor, self.threshold_factor, 0, fft_length)
else:
#thresholds = [self.threshold_factor, 9e-5]
self.slice = gr.threshold_ff(threshold, threshold, 0, fft_length, threshold_type, threshold_gap)
self.connect(self.input, self.crosscorr_filter, self.corrmag, self.slice, self.f2b)
# some debug dump #
self.connect(self.corrmag, gr.file_sink(gr.sizeof_float, "ofdm_corrmag.dat"))
#self.connect(self.f2b, gr.file_sink(gr.sizeof_char, "ofdm_f2b.dat"))
self.connect(self.f2b, (self.sample_and_hold,1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self,0))
#self.connect(self.pk_detect, (self,1)) #removed
#self.connect(self.f2b, gr.delay(gr.sizeof_char, 1), (self, 1))
self.connect(self.f2b, (self, 1))
if logging:
self.connect(self.matched_filter, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-mf_f.dat"))
self.connect(self.normalize, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-theta_f.dat"))
self.connect(self.angle, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-epsilon_f.dat"))
self.connect(self.pk_detect, gr.file_sink(gr.sizeof_char, "ofdm_sync_pn-peaks_b.dat"))
self.connect(self.sample_and_hold, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-sample_and_hold_f.dat"))
self.connect(self.input, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_pn-input_c.dat"))
def __init__(self, vlen):
gr.hier_block2.__init__(
self, "snr_estimator",
gr.io_signature2(2, 2, gr.sizeof_gr_complex, gr.sizeof_char),
gr.io_signature(1, 1, gr.sizeof_float))
data_in = (self, 0)
trig_in = (self, 1)
snr_out = (self, 0)
## Preamble Extraction
sampler = vector_sampler(gr.sizeof_gr_complex, vlen)
self.connect(data_in, sampler)
self.connect(trig_in, (sampler, 1))
## Algorithm implementation
estim = sc_snr_estimator(vlen)
self.connect(sampler, estim)
self.connect(estim, snr_out)
return
## Split block into two parts
splitter = gr.vector_to_streams(gr.sizeof_gr_complex * vlen / 2, 2)
self.connect(sampler, splitter)
## Conjugate first half block
conj = gr.conjugate_cc(vlen / 2)
self.connect(splitter, conj)
## Vector multiplication of both half blocks
vmult = gr.multiply_vcc(vlen / 2)
self.connect(conj, vmult)
self.connect((splitter, 1), (vmult, 1))
## Sum of Products
psum = vector_sum_vcc(vlen / 2)
self.connect(vmult, psum)
## Magnitude of P(d)
p_mag = gr.complex_to_mag()
self.connect(psum, p_mag)
## Squared Magnitude of block
r_magsqrd = gr.complex_to_mag_squared(vlen)
self.connect(sampler, r_magsqrd)
## Sum of squared second half block
r_sum = vector_sum_vff(vlen)
self.connect(r_magsqrd, r_sum)
## Square Root of Metric
m_sqrt = gr.divide_ff()
self.connect(p_mag, (m_sqrt, 0))
self.connect(r_sum, gr.multiply_const_ff(0.5), (m_sqrt, 1))
## Denominator of SNR estimate
denom = gr.add_const_ff(1)
neg_m_sqrt = gr.multiply_const_ff(-1.0)
self.connect(m_sqrt, limit_vff(1, 1 - 2e-5, -1000), neg_m_sqrt, denom)
## SNR estimate
snr_est = gr.divide_ff()
self.connect(m_sqrt, (snr_est, 0))
self.connect(denom, (snr_est, 1))
## Setup Output Connections
self.connect(snr_est, self)
def __init__(self, fft_length, cp_length, half_sync, logging=False):
gr.hier_block2.__init__(
self,
"ofdm_sync_pn",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature3(
3,
3, # Output signature
gr.sizeof_gr_complex, # delayed input
gr.sizeof_float, # fine frequency offset
gr.sizeof_char # timing indicator
))
if half_sync:
period = fft_length / 2
window = fft_length / 2
else: # full symbol
period = fft_length + cp_length
window = fft_length # makes the plateau cp_length long
# Calculate the frequency offset from the correlation of the preamble
x_corr = gr.multiply_cc()
self.connect(self, gr.conjugate_cc(), (x_corr, 0))
self.connect(self, gr.delay(gr.sizeof_gr_complex, period), (x_corr, 1))
P_d = gr.moving_average_cc(window, 1.0)
self.connect(x_corr, P_d)
P_d_angle = gr.complex_to_arg()
self.connect(P_d, P_d_angle)
# Get the power of the input signal to normalize the output of the correlation
R_d = gr.moving_average_ff(window, 1.0)
self.connect(self, gr.complex_to_mag_squared(), R_d)
R_d_squared = gr.multiply_ff() # this is retarded
self.connect(R_d, (R_d_squared, 0))
self.connect(R_d, (R_d_squared, 1))
M_d = gr.divide_ff()
self.connect(P_d, gr.complex_to_mag_squared(), (M_d, 0))
self.connect(R_d_squared, (M_d, 1))
# Now we need to detect peak of M_d
# NOTE: replaced fir_filter with moving_average for clarity
# the peak is up to cp_length long, but noisy, so average it out
#matched_filter_taps = [1.0/cp_length for i in range(cp_length)]
#matched_filter = gr.fir_filter_fff(1, matched_filter_taps)
matched_filter = gr.moving_average_ff(cp_length, 1.0 / cp_length)
# NOTE: the look_ahead parameter doesn't do anything
# these parameters are kind of magic, increase 1 and 2 (==) to be more tolerant
#peak_detect = raw.peak_detector_fb(0.55, 0.55, 30, 0.001)
peak_detect = raw.peak_detector_fb(0.25, 0.25, 30, 0.001)
# NOTE: gr.peak_detector_fb is broken!
#peak_detect = gr.peak_detector_fb(0.55, 0.55, 30, 0.001)
#peak_detect = gr.peak_detector_fb(0.45, 0.45, 30, 0.001)
#peak_detect = gr.peak_detector_fb(0.30, 0.30, 30, 0.001)
# offset by -1
self.connect(M_d, matched_filter, gr.add_const_ff(-1), peak_detect)
# peak_detect indicates the time M_d is highest, which is the end of the symbol.
# We should try to sample in the middle of the plateau!!
# FIXME until we figure out how to do this, just offset by cp_length/2
offset = 6 #cp_length/2
# nco(t) = P_d_angle(t-offset) sampled at peak_detect(t)
# modulate input(t - fft_length) by nco(t)
# signal to sample input(t) at t-offset
#
# We can't delay by < 0 so instead:
# input is delayed by fft_length
# P_d_angle is delayed by offset
# signal to sample is delayed by fft_length - offset
#
phi = gr.sample_and_hold_ff()
self.connect(peak_detect, (phi, 1))
self.connect(P_d_angle, gr.delay(gr.sizeof_float, offset), (phi, 0))
#self.connect(P_d_angle, matched_filter2, (phi,0)) # why isn't this better?!?
# FIXME: we add fft_length delay so that the preamble is nco corrected too
# BUT is this buffering worth it? consider implementing sync as a proper block
# delay the input signal to follow the frequency offset signal
self.connect(self, gr.delay(gr.sizeof_gr_complex,
(fft_length + offset)), (self, 0))
self.connect(phi, (self, 1))
self.connect(peak_detect, (self, 2))
if logging:
self.connect(matched_filter,
gr.file_sink(gr.sizeof_float, "sync-mf.dat"))
self.connect(M_d, gr.file_sink(gr.sizeof_float, "sync-M.dat"))
self.connect(P_d_angle,
gr.file_sink(gr.sizeof_float, "sync-angle.dat"))
self.connect(peak_detect,
gr.file_sink(gr.sizeof_char, "sync-peaks.datb"))
self.connect(phi, gr.file_sink(gr.sizeof_float, "sync-phi.dat"))
def __init__(self, *args, **kwds):
# begin wxGlade: MyFrame.__init__
kwds["style"] = wx.DEFAULT_FRAME_STYLE
wx.Frame.__init__(self, *args, **kwds)
# Menu Bar
self.frame_1_menubar = wx.MenuBar()
self.SetMenuBar(self.frame_1_menubar)
wxglade_tmp_menu = wx.Menu()
self.Exit = wx.MenuItem(wxglade_tmp_menu, ID_EXIT, "Exit", "Exit", wx.ITEM_NORMAL)
wxglade_tmp_menu.AppendItem(self.Exit)
self.frame_1_menubar.Append(wxglade_tmp_menu, "File")
# Menu Bar end
self.panel_1 = wx.Panel(self, -1)
self.button_1 = wx.Button(self, ID_BUTTON_1, "LSB")
self.button_2 = wx.Button(self, ID_BUTTON_2, "USB")
self.button_3 = wx.Button(self, ID_BUTTON_3, "AM")
self.button_4 = wx.Button(self, ID_BUTTON_4, "CW")
self.button_5 = wx.ToggleButton(self, ID_BUTTON_5, "Upper")
self.slider_1 = wx.Slider(self, ID_SLIDER_1, 0, -15799, 15799, style=wx.SL_HORIZONTAL | wx.SL_LABELS)
self.button_6 = wx.ToggleButton(self, ID_BUTTON_6, "Lower")
self.slider_2 = wx.Slider(self, ID_SLIDER_2, 0, -15799, 15799, style=wx.SL_HORIZONTAL | wx.SL_LABELS)
self.panel_5 = wx.Panel(self, -1)
self.label_1 = wx.StaticText(self, -1, " Band\nCenter")
self.text_ctrl_1 = wx.TextCtrl(self, ID_TEXT_1, "")
self.panel_6 = wx.Panel(self, -1)
self.panel_7 = wx.Panel(self, -1)
self.panel_2 = wx.Panel(self, -1)
self.button_7 = wx.ToggleButton(self, ID_BUTTON_7, "Freq")
self.slider_3 = wx.Slider(self, ID_SLIDER_3, 3000, 0, 6000)
self.spin_ctrl_1 = wx.SpinCtrl(self, ID_SPIN_1, "", min=0, max=100)
self.button_8 = wx.ToggleButton(self, ID_BUTTON_8, "Vol")
self.slider_4 = wx.Slider(self, ID_SLIDER_4, 0, 0, 500)
self.slider_5 = wx.Slider(self, ID_SLIDER_5, 0, 0, 20)
self.button_9 = wx.ToggleButton(self, ID_BUTTON_9, "Time")
self.button_11 = wx.Button(self, ID_BUTTON_11, "Rew")
self.button_10 = wx.Button(self, ID_BUTTON_10, "Fwd")
self.panel_3 = wx.Panel(self, -1)
self.label_2 = wx.StaticText(self, -1, "PGA ")
self.panel_4 = wx.Panel(self, -1)
self.panel_8 = wx.Panel(self, -1)
self.panel_9 = wx.Panel(self, -1)
self.label_3 = wx.StaticText(self, -1, "AM Sync\nCarrier")
self.slider_6 = wx.Slider(self, ID_SLIDER_6, 50, 0, 200, style=wx.SL_HORIZONTAL | wx.SL_LABELS)
self.label_4 = wx.StaticText(self, -1, "Antenna Tune")
self.slider_7 = wx.Slider(self, ID_SLIDER_7, 1575, 950, 2200, style=wx.SL_HORIZONTAL | wx.SL_LABELS)
self.panel_10 = wx.Panel(self, -1)
self.button_12 = wx.ToggleButton(self, ID_BUTTON_12, "Auto Tune")
self.button_13 = wx.Button(self, ID_BUTTON_13, "Calibrate")
self.button_14 = wx.Button(self, ID_BUTTON_14, "Reset")
self.panel_11 = wx.Panel(self, -1)
self.panel_12 = wx.Panel(self, -1)
self.__set_properties()
self.__do_layout()
# end wxGlade
parser = OptionParser(option_class=eng_option)
parser.add_option(
"-c", "--ddc-freq", type="eng_float", default=3.9e6, help="set Rx DDC frequency to FREQ", metavar="FREQ"
)
parser.add_option("-a", "--audio_file", default="", help="audio output file", metavar="FILE")
parser.add_option("-r", "--radio_file", default="", help="radio output file", metavar="FILE")
parser.add_option("-i", "--input_file", default="", help="radio input file", metavar="FILE")
parser.add_option("-d", "--decim", type="int", default=250, help="USRP decimation")
parser.add_option(
"-R",
"--rx-subdev-spec",
type="subdev",
default=None,
help="select USRP Rx side A or B (default=first one with a daughterboard)",
)
(options, args) = parser.parse_args()
self.usrp_center = options.ddc_freq
usb_rate = 64e6 / options.decim
self.slider_range = usb_rate * 0.9375
self.f_lo = self.usrp_center - (self.slider_range / 2)
self.f_hi = self.usrp_center + (self.slider_range / 2)
self.af_sample_rate = 32000
fir_decim = long(usb_rate / self.af_sample_rate)
# data point arrays for antenna tuner
self.xdata = []
self.ydata = []
self.tb = gr.top_block()
# radio variables, initial conditions
self.frequency = self.usrp_center
# these map the frequency slider (0-6000) to the actual range
self.f_slider_offset = self.f_lo
self.f_slider_scale = 10000 / options.decim
self.spin_ctrl_1.SetRange(self.f_lo, self.f_hi)
self.text_ctrl_1.SetValue(str(int(self.usrp_center)))
self.slider_5.SetValue(0)
self.AM_mode = False
self.slider_3.SetValue((self.frequency - self.f_slider_offset) / self.f_slider_scale)
self.spin_ctrl_1.SetValue(int(self.frequency))
POWERMATE = True
try:
self.pm = powermate.powermate(self)
except:
sys.stderr.write("Unable to find PowerMate or Contour Shuttle\n")
POWERMATE = False
if POWERMATE:
powermate.EVT_POWERMATE_ROTATE(self, self.on_rotate)
powermate.EVT_POWERMATE_BUTTON(self, self.on_pmButton)
self.active_button = 7
# command line options
if options.audio_file == "":
SAVE_AUDIO_TO_FILE = False
else:
SAVE_AUDIO_TO_FILE = True
if options.radio_file == "":
SAVE_RADIO_TO_FILE = False
else:
SAVE_RADIO_TO_FILE = True
if options.input_file == "":
self.PLAY_FROM_USRP = True
else:
self.PLAY_FROM_USRP = False
if self.PLAY_FROM_USRP:
self.src = usrp.source_s(decim_rate=options.decim)
if options.rx_subdev_spec is None:
options.rx_subdev_spec = pick_subdevice(self.src)
self.src.set_mux(usrp.determine_rx_mux_value(self.src, options.rx_subdev_spec))
self.subdev = usrp.selected_subdev(self.src, options.rx_subdev_spec)
self.src.tune(0, self.subdev, self.usrp_center)
self.tune_offset = 0 # -self.usrp_center - self.src.rx_freq(0)
else:
self.src = gr.file_source(gr.sizeof_short, options.input_file)
self.tune_offset = 2200 # 2200 works for 3.5-4Mhz band
# save radio data to a file
if SAVE_RADIO_TO_FILE:
file = gr.file_sink(gr.sizeof_short, options.radio_file)
self.tb.connect(self.src, file)
# 2nd DDC
xlate_taps = gr.firdes.low_pass(1.0, usb_rate, 16e3, 4e3, gr.firdes.WIN_HAMMING)
self.xlate = gr.freq_xlating_fir_filter_ccf(fir_decim, xlate_taps, self.tune_offset, usb_rate)
# convert rf data in interleaved short int form to complex
s2ss = gr.stream_to_streams(gr.sizeof_short, 2)
s2f1 = gr.short_to_float()
s2f2 = gr.short_to_float()
src_f2c = gr.float_to_complex()
self.tb.connect(self.src, s2ss)
self.tb.connect((s2ss, 0), s2f1)
self.tb.connect((s2ss, 1), s2f2)
self.tb.connect(s2f1, (src_f2c, 0))
self.tb.connect(s2f2, (src_f2c, 1))
# Complex Audio filter
audio_coeffs = gr.firdes.complex_band_pass(
1.0, # gain
self.af_sample_rate, # sample rate
-3000, # low cutoff
0, # high cutoff
100, # transition
gr.firdes.WIN_HAMMING,
) # window
self.slider_1.SetValue(0)
self.slider_2.SetValue(-3000)
self.audio_filter = gr.fir_filter_ccc(1, audio_coeffs)
# Main +/- 16Khz spectrum display
self.fft = fftsink2.fft_sink_c(
self.panel_2, fft_size=512, sample_rate=self.af_sample_rate, average=True, size=(640, 240)
)
# AM Sync carrier
if AM_SYNC_DISPLAY:
self.fft2 = fftsink.fft_sink_c(
self.tb,
self.panel_9,
y_per_div=20,
fft_size=512,
sample_rate=self.af_sample_rate,
average=True,
size=(640, 240),
)
c2f = gr.complex_to_float()
# AM branch
self.sel_am = gr.multiply_const_cc(0)
# the following frequencies turn out to be in radians/sample
# gr.pll_refout_cc(alpha,beta,min_freq,max_freq)
# suggested alpha = X, beta = .25 * X * X
pll = gr.pll_refout_cc(
0.5, 0.0625, (2.0 * math.pi * 7.5e3 / self.af_sample_rate), (2.0 * math.pi * 6.5e3 / self.af_sample_rate)
)
self.pll_carrier_scale = gr.multiply_const_cc(complex(10, 0))
am_det = gr.multiply_cc()
# these are for converting +7.5kHz to -7.5kHz
# for some reason gr.conjugate_cc() adds noise ??
c2f2 = gr.complex_to_float()
c2f3 = gr.complex_to_float()
f2c = gr.float_to_complex()
phaser1 = gr.multiply_const_ff(1)
phaser2 = gr.multiply_const_ff(-1)
# filter for pll generated carrier
pll_carrier_coeffs = gr.firdes.complex_band_pass(
2.0, # gain
self.af_sample_rate, # sample rate
7400, # low cutoff
7600, # high cutoff
100, # transition
gr.firdes.WIN_HAMMING,
) # window
self.pll_carrier_filter = gr.fir_filter_ccc(1, pll_carrier_coeffs)
self.sel_sb = gr.multiply_const_ff(1)
combine = gr.add_ff()
# AGC
sqr1 = gr.multiply_ff()
intr = gr.iir_filter_ffd([0.004, 0], [0, 0.999])
offset = gr.add_const_ff(1)
agc = gr.divide_ff()
self.scale = gr.multiply_const_ff(0.00001)
dst = audio.sink(long(self.af_sample_rate))
self.tb.connect(src_f2c, self.xlate, self.fft)
self.tb.connect(self.xlate, self.audio_filter, self.sel_am, (am_det, 0))
self.tb.connect(self.sel_am, pll, self.pll_carrier_scale, self.pll_carrier_filter, c2f3)
self.tb.connect((c2f3, 0), phaser1, (f2c, 0))
self.tb.connect((c2f3, 1), phaser2, (f2c, 1))
self.tb.connect(f2c, (am_det, 1))
self.tb.connect(am_det, c2f2, (combine, 0))
self.tb.connect(self.audio_filter, c2f, self.sel_sb, (combine, 1))
if AM_SYNC_DISPLAY:
self.tb.connect(self.pll_carrier_filter, self.fft2)
self.tb.connect(combine, self.scale)
self.tb.connect(self.scale, (sqr1, 0))
self.tb.connect(self.scale, (sqr1, 1))
self.tb.connect(sqr1, intr, offset, (agc, 1))
self.tb.connect(self.scale, (agc, 0))
self.tb.connect(agc, dst)
if SAVE_AUDIO_TO_FILE:
f_out = gr.file_sink(gr.sizeof_short, options.audio_file)
sc1 = gr.multiply_const_ff(64000)
f2s1 = gr.float_to_short()
self.tb.connect(agc, sc1, f2s1, f_out)
self.tb.start()
# for mouse position reporting on fft display
em.eventManager.Register(self.Mouse, wx.EVT_MOTION, self.fft.win)
# and left click to re-tune
em.eventManager.Register(self.Click, wx.EVT_LEFT_DOWN, self.fft.win)
# start a timer to check for web commands
if WEB_CONTROL:
self.timer = UpdateTimer(self, 1000) # every 1000 mSec, 1 Sec
wx.EVT_BUTTON(self, ID_BUTTON_1, self.set_lsb)
wx.EVT_BUTTON(self, ID_BUTTON_2, self.set_usb)
wx.EVT_BUTTON(self, ID_BUTTON_3, self.set_am)
wx.EVT_BUTTON(self, ID_BUTTON_4, self.set_cw)
wx.EVT_BUTTON(self, ID_BUTTON_10, self.fwd)
wx.EVT_BUTTON(self, ID_BUTTON_11, self.rew)
wx.EVT_BUTTON(self, ID_BUTTON_13, self.AT_calibrate)
wx.EVT_BUTTON(self, ID_BUTTON_14, self.AT_reset)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_5, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_6, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_7, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_8, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_9, self.on_button)
wx.EVT_SLIDER(self, ID_SLIDER_1, self.set_filter)
wx.EVT_SLIDER(self, ID_SLIDER_2, self.set_filter)
wx.EVT_SLIDER(self, ID_SLIDER_3, self.slide_tune)
wx.EVT_SLIDER(self, ID_SLIDER_4, self.set_volume)
wx.EVT_SLIDER(self, ID_SLIDER_5, self.set_pga)
wx.EVT_SLIDER(self, ID_SLIDER_6, self.am_carrier)
wx.EVT_SLIDER(self, ID_SLIDER_7, self.antenna_tune)
wx.EVT_SPINCTRL(self, ID_SPIN_1, self.spin_tune)
wx.EVT_MENU(self, ID_EXIT, self.TimeToQuit)
def __init__(self,
fft_length,
cp_length,
kstime,
threshold,
threshold_type,
threshold_gap,
logging=False):
"""
OFDM synchronization using PN Correlation:
T. M. Schmidl and D. C. Cox, "Robust Frequency and Timing
Synchonization for OFDM," IEEE Trans. Communications, vol. 45,
no. 12, 1997.
"""
gr.hier_block2.__init__(
self,
"ofdm_sync_pn",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float,
gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
# PN Sync
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length / 2)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc()
self.corr = gr.multiply_cc()
# Create a moving sum filter for the corr output
if 1:
moving_sum_taps = [1.0 for i in range(fft_length // 2)]
self.moving_sum_filter = gr.fir_filter_ccf(1, moving_sum_taps)
else:
moving_sum_taps = [
complex(1.0, 0.0) for i in range(fft_length // 2)
]
self.moving_sum_filter = gr.fft_filter_ccc(1, moving_sum_taps)
# Create a moving sum filter for the input
self.inputmag2 = gr.complex_to_mag_squared()
movingsum2_taps = [1.0 for i in range(fft_length // 2)]
#movingsum2_taps = [0.5 for i in range(fft_length*4)] #apurv - implementing Veljo's suggestion, when pause b/w packets
if 1:
self.inputmovingsum = gr.fir_filter_fff(1, movingsum2_taps)
else:
self.inputmovingsum = gr.fft_filter_fff(1, movingsum2_taps)
self.square = gr.multiply_ff()
self.normalize = gr.divide_ff()
# Get magnitude (peaks) and angle (phase/freq error)
self.c2mag = gr.complex_to_mag_squared()
self.angle = gr.complex_to_arg()
self.sample_and_hold = gr.sample_and_hold_ff()
#ML measurements input to sampler block and detect
self.sub1 = gr.add_const_ff(-1)
self.pk_detect = gr.peak_detector_fb(
0.20, 0.20, 30, 0.001
) #apurv - implementing Veljo's suggestion, when pause b/w packets
self.connect(self, self.input)
# Calculate the frequency offset from the correlation of the preamble
self.connect(self.input, self.delay)
self.connect(self.input, (self.corr, 0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr, 1))
self.connect(self.corr, self.moving_sum_filter)
#self.connect(self.moving_sum_filter, self.c2mag)
self.connect(self.moving_sum_filter, self.angle)
self.connect(self.angle, (self.sample_and_hold, 0)) # apurv--
#self.connect(self.angle, gr.delay(gr.sizeof_float, offset), (self.sample_and_hold, 0)) #apurv++
cross_correlate = 1
if cross_correlate == 1:
# cross-correlate with the known symbol
kstime = [k.conjugate() for k in kstime]
kstime.reverse()
self.crosscorr_filter = gr.fir_filter_ccc(1, kstime)
# get the magnitude #
self.corrmag = gr.complex_to_mag_squared()
self.f2b = gr.float_to_char()
self.threshold_factor = threshold #0.0012 #0.012 #0.0015
if 0:
self.slice = gr.threshold_ff(self.threshold_factor,
self.threshold_factor, 0,
fft_length)
else:
#thresholds = [self.threshold_factor, 9e-5]
self.slice = gr.threshold_ff(threshold, threshold, 0,
fft_length, threshold_type,
threshold_gap)
self.connect(self.input, self.crosscorr_filter, self.corrmag,
self.slice, self.f2b)
# some debug dump #
self.connect(self.corrmag,
gr.file_sink(gr.sizeof_float, "ofdm_corrmag.dat"))
#self.connect(self.f2b, gr.file_sink(gr.sizeof_char, "ofdm_f2b.dat"))
self.connect(self.f2b, (self.sample_and_hold, 1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self, 0))
#self.connect(self.pk_detect, (self,1)) #removed
#self.connect(self.f2b, gr.delay(gr.sizeof_char, 1), (self, 1))
self.connect(self.f2b, (self, 1))
if logging:
self.connect(
self.matched_filter,
gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-mf_f.dat"))
self.connect(
self.normalize,
gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-theta_f.dat"))
self.connect(
self.angle,
gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-epsilon_f.dat"))
self.connect(
self.pk_detect,
gr.file_sink(gr.sizeof_char, "ofdm_sync_pn-peaks_b.dat"))
self.connect(
self.sample_and_hold,
gr.file_sink(gr.sizeof_float,
"ofdm_sync_pn-sample_and_hold_f.dat"))
self.connect(
self.input,
gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_pn-input_c.dat"))
def __init__(self, fft_length, cp_length, logging=False):
"""
OFDM synchronization using PN Correlation:
T. M. Schmidl and D. C. Cox, "Robust Frequency and Timing
Synchonization for OFDM," IEEE Trans. Communications, vol. 45,
no. 12, 1997.
"""
gr.hier_block2.__init__(self, "ofdm_sync_pn",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
# PN Sync
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length/2)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc();
self.corr = gr.multiply_cc();
# Create a moving sum filter for the corr output
if 1:
moving_sum_taps = [1.0 for i in range(fft_length//2)]
self.moving_sum_filter = gr.fir_filter_ccf(1,moving_sum_taps)
else:
moving_sum_taps = [complex(1.0,0.0) for i in range(fft_length//2)]
self.moving_sum_filter = gr.fft_filter_ccc(1,moving_sum_taps)
# Create a moving sum filter for the input
self.inputmag2 = gr.complex_to_mag_squared()
# Modified by Yong (12.06.27)
#movingsum2_taps = [1.0 for i in range(fft_length//2)]
movingsum2_taps = [0.5 for i in range(fft_length)]
if 1:
self.inputmovingsum = gr.fir_filter_fff(1,movingsum2_taps)
else:
self.inputmovingsum = gr.fft_filter_fff(1,movingsum2_taps)
self.square = gr.multiply_ff()
self.normalize = gr.divide_ff()
# Get magnitude (peaks) and angle (phase/freq error)
self.c2mag = gr.complex_to_mag_squared()
self.angle = gr.complex_to_arg()
self.sample_and_hold = gr.sample_and_hold_ff()
#ML measurements input to sampler block and detect
self.sub1 = gr.add_const_ff(-1)
self.pk_detect = gr.peak_detector_fb(0.20, 0.20, 30, 0.001)
#self.pk_detect = gr.peak_detector2_fb(9)
self.connect(self, self.input)
# Calculate the frequency offset from the correlation of the preamble
self.connect(self.input, self.delay)
self.connect(self.input, (self.corr,0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr,1))
self.connect(self.corr, self.moving_sum_filter)
self.connect(self.moving_sum_filter, self.c2mag)
self.connect(self.moving_sum_filter, self.angle)
self.connect(self.angle, (self.sample_and_hold,0))
# Get the power of the input signal to normalize the output of the correlation
self.connect(self.input, self.inputmag2, self.inputmovingsum)
self.connect(self.inputmovingsum, (self.square,0))
self.connect(self.inputmovingsum, (self.square,1))
self.connect(self.square, (self.normalize,1))
self.connect(self.c2mag, (self.normalize,0))
# Create a moving sum filter for the corr output
matched_filter_taps = [1.0/cp_length for i in range(cp_length)]
self.matched_filter = gr.fir_filter_fff(1,matched_filter_taps)
self.connect(self.normalize, self.matched_filter)
self.connect(self.matched_filter, self.sub1, self.pk_detect)
#self.connect(self.matched_filter, self.pk_detect)
self.connect(self.pk_detect, (self.sample_and_hold,1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self,0))
self.connect(self.pk_detect, (self,1))
if logging:
self.connect(self.matched_filter, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-mf_f.dat"))
self.connect(self.c2mag, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-nominator_f.dat"))
self.connect(self.square, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-denominator_f.dat"))
self.connect(self.normalize, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-theta_f.dat"))
self.connect(self.angle, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-epsilon_f.dat"))
self.connect(self.pk_detect, gr.file_sink(gr.sizeof_char, "ofdm_sync_pn-peaks_b.dat"))
self.connect(self.sample_and_hold, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-sample_and_hold_f.dat"))
self.connect(self.input, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_pn-input_c.dat"))
def __init__(self, options, hostname):
gr.top_block.__init__(self)
##################################################
# Variables
##################################################
window_size = options.window_size
sync_length = options.sync_length
gain = options.gain
freq = options.freq
samp_rate = options.bandwidth
self.uhd_usrp_source_0 = uhd.usrp_source(device_addr="", stream_args=uhd.stream_args(cpu_format="fc32", channels=range(1)))
self.uhd_usrp_source_0.set_samp_rate(samp_rate)
self.uhd_usrp_source_0.set_center_freq(freq, 0)
self.uhd_usrp_source_0.set_gain(gain, 0)
self.ieee802_1_ofdm_sync_short_0 = gr_ieee802_11.ofdm_sync_short(0.8, 80 * 80, 2, False)
self.ieee802_1_ofdm_sync_long_0 = gr_ieee802_11.ofdm_sync_long(sync_length, 100, False)
self.ieee802_1_ofdm_equalize_symbols_0 = gr_ieee802_11.ofdm_equalize_symbols(False)
self.ieee802_1_ofdm_decode_signal_0 = gr_ieee802_11.ofdm_decode_signal(False)
self.ieee802_1_ofdm_decode_mac_0 = gr_ieee802_11.ofdm_decode_mac(False)
self.ieee802_11_ofdm_parse_mac_0 = gr_ieee802_11.ofdm_parse_mac(True)
self.gr_stream_to_vector_0 = gr.stream_to_vector(gr.sizeof_gr_complex*1, 64)
self.gr_socket_pdu_0 = gr.socket_pdu("TCP_SERVER", hostname, str(options.PHYRXport), 10000)
self.gr_skiphead_0 = gr.skiphead(gr.sizeof_gr_complex*1, 20000000)
self.gr_multiply_xx_0 = gr.multiply_vcc(1)
self.gr_divide_xx_0 = gr.divide_ff(1)
self.gr_delay_0_0 = gr.delay(gr.sizeof_gr_complex*1, sync_length)
self.gr_delay_0 = gr.delay(gr.sizeof_gr_complex*1, 16)
self.gr_conjugate_cc_0 = gr.conjugate_cc()
self.gr_complex_to_mag_squared_0 = gr.complex_to_mag_squared(1)
self.gr_complex_to_mag_0 = gr.complex_to_mag(1)
self.fir_filter_xxx_0_0 = filter.fir_filter_ccf(1, ([1]*window_size))
self.fir_filter_xxx_0 = filter.fir_filter_fff(1, ([1]*window_size))
self.fft_vxx_0 = fft.fft_vcc(64, True, (), True, 1)
self.message_debug = gr.message_debug()
##################################################
# Connections
##################################################
self.connect((self.uhd_usrp_source_0, 0), (self.gr_skiphead_0, 0))
self.connect((self.gr_skiphead_0, 0), (self.gr_complex_to_mag_squared_0, 0))
self.connect((self.fir_filter_xxx_0, 0), (self.gr_divide_xx_0, 1))
self.connect((self.gr_complex_to_mag_squared_0, 0), (self.fir_filter_xxx_0, 0))
self.connect((self.gr_skiphead_0, 0), (self.gr_multiply_xx_0, 0))
self.connect((self.gr_conjugate_cc_0, 0), (self.gr_multiply_xx_0, 1))
self.connect((self.gr_complex_to_mag_0, 0), (self.gr_divide_xx_0, 0))
self.connect((self.gr_multiply_xx_0, 0), (self.fir_filter_xxx_0_0, 0))
self.connect((self.fir_filter_xxx_0_0, 0), (self.gr_complex_to_mag_0, 0))
self.connect((self.gr_skiphead_0, 0), (self.gr_delay_0, 0))
self.connect((self.gr_delay_0, 0), (self.gr_conjugate_cc_0, 0))
self.connect((self.fft_vxx_0, 0), (self.ieee802_1_ofdm_equalize_symbols_0, 0))
self.connect((self.ieee802_1_ofdm_equalize_symbols_0, 0), (self.ieee802_1_ofdm_decode_signal_0, 0))
self.connect((self.ieee802_1_ofdm_decode_signal_0, 0), (self.ieee802_1_ofdm_decode_mac_0, 0))
self.connect((self.ieee802_1_ofdm_sync_short_0, 0), (self.gr_delay_0_0, 0))
self.connect((self.gr_delay_0, 0), (self.ieee802_1_ofdm_sync_short_0, 0))
self.connect((self.gr_divide_xx_0, 0), (self.ieee802_1_ofdm_sync_short_0, 1))
self.connect((self.gr_delay_0_0, 0), (self.ieee802_1_ofdm_sync_long_0, 1))
self.connect((self.ieee802_1_ofdm_sync_short_0, 0), (self.ieee802_1_ofdm_sync_long_0, 0))
self.connect((self.ieee802_1_ofdm_sync_long_0, 0), (self.gr_stream_to_vector_0, 0))
self.connect((self.gr_stream_to_vector_0, 0), (self.fft_vxx_0, 0))
##################################################
# Asynch Message Connections
##################################################
self.msg_connect(self.ieee802_1_ofdm_decode_mac_0, "out", self.ieee802_11_ofdm_parse_mac_0, "in")
self.msg_connect(self.ieee802_11_ofdm_parse_mac_0, "out", self.gr_socket_pdu_0, "pdus")
def __init__(self, subc, vlen, ss):
gr.hier_block2.__init__(self, "new_snr_estimator",
gr.io_signature(1,1,gr.sizeof_gr_complex*vlen),
gr.io_signature(1,1,gr.sizeof_float))
print "Created Milan's SNR estimator"
trigger = [0]*vlen
trigger[0] = 1
u = range (vlen/ss*(ss-1))
zeros_ind= map(lambda z: z+1+z/(ss-1),u)
skip1 = skip(gr.sizeof_gr_complex,vlen)
for x in zeros_ind:
skip1.skip(x)
#print "skipped zeros",zeros_ind
v = range (vlen/ss)
ones_ind= map(lambda z: z*ss,v)
skip2 = skip(gr.sizeof_gr_complex,vlen)
for x in ones_ind:
skip2.skip(x)
#print "skipped ones",ones_ind
v2s = gr.vector_to_stream(gr.sizeof_gr_complex,vlen)
s2v1 = gr.stream_to_vector(gr.sizeof_gr_complex,vlen/ss)
trigger_src_1 = gr.vector_source_b(trigger,True)
s2v2 = gr.stream_to_vector(gr.sizeof_gr_complex,vlen/ss*(ss-1))
trigger_src_2 = gr.vector_source_b(trigger,True)
mag_sq_ones = gr.complex_to_mag_squared(vlen/ss)
mag_sq_zeros = gr.complex_to_mag_squared(vlen/ss*(ss-1))
filt_ones = gr.single_pole_iir_filter_ff(0.1,vlen/ss)
filt_zeros = gr.single_pole_iir_filter_ff(0.1,vlen/ss*(ss-1))
sum_ones = vector_sum_vff(vlen/ss)
sum_zeros = vector_sum_vff(vlen/ss*(ss-1))
D = gr.divide_ff()
P = gr.multiply_ff()
mult1 = gr.multiply_const_ff(ss-1.0)
add1 = gr.add_const_ff(-1.0)
mult2 = gr.multiply_const_ff(1./ss)
scsnrdb = gr.nlog10_ff(10,1,0)
filt_end = gr.single_pole_iir_filter_ff(0.1)
self.connect(self,v2s,skip1,s2v1,mag_sq_ones,filt_ones,sum_ones)
self.connect(trigger_src_1,(skip1,1))
self.connect(v2s,skip2,s2v2,mag_sq_zeros,filt_zeros,sum_zeros)
self.connect(trigger_src_2,(skip2,1))
self.connect(sum_ones,D)
self.connect(sum_zeros,(D,1))
self.connect(D,mult1,add1,mult2)
self.connect(mult2,scsnrdb,filt_end,self)
def test_div_ff_1(self):
src1_data = (1, 2, 4, -8)
expected_result = (1, 0.5, 0.25, -.125)
op = gr.divide_ff()
self.help_ff((src1_data, ), expected_result, op)
def __init__(self,
freq_corr=0,
N_id_1=134,
avg_frames=1,
N_id_2=0,
decim=16):
grc_wxgui.top_block_gui.__init__(self, title="Sss Corr2 Gui")
_icon_path = "/usr/share/icons/hicolor/32x32/apps/gnuradio-grc.png"
self.SetIcon(wx.Icon(_icon_path, wx.BITMAP_TYPE_ANY))
##################################################
# Parameters
##################################################
self.freq_corr = freq_corr
self.N_id_1 = N_id_1
self.avg_frames = avg_frames
self.N_id_2 = N_id_2
self.decim = decim
##################################################
# Variables
##################################################
self.vec_half_frame = vec_half_frame = 30720 * 5 / decim
self.samp_rate = samp_rate = 30720e3 / decim
self.rot = rot = 0
self.noise_level = noise_level = 0
self.fft_size = fft_size = 2048 / decim
##################################################
# Blocks
##################################################
_rot_sizer = wx.BoxSizer(wx.VERTICAL)
self._rot_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_rot_sizer,
value=self.rot,
callback=self.set_rot,
label='rot',
converter=forms.float_converter(),
proportion=0,
)
self._rot_slider = forms.slider(
parent=self.GetWin(),
sizer=_rot_sizer,
value=self.rot,
callback=self.set_rot,
minimum=0,
maximum=1,
num_steps=100,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.Add(_rot_sizer)
_noise_level_sizer = wx.BoxSizer(wx.VERTICAL)
self._noise_level_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_noise_level_sizer,
value=self.noise_level,
callback=self.set_noise_level,
label='noise_level',
converter=forms.float_converter(),
proportion=0,
)
self._noise_level_slider = forms.slider(
parent=self.GetWin(),
sizer=_noise_level_sizer,
value=self.noise_level,
callback=self.set_noise_level,
minimum=0,
maximum=10,
num_steps=100,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.Add(_noise_level_sizer)
self.wxgui_scopesink2_0 = scopesink2.scope_sink_c(
self.GetWin(),
title="Scope Plot",
sample_rate=samp_rate,
v_scale=0,
v_offset=0,
t_scale=0,
ac_couple=False,
xy_mode=False,
num_inputs=2,
trig_mode=gr.gr_TRIG_MODE_AUTO,
y_axis_label="Counts",
)
self.Add(self.wxgui_scopesink2_0.win)
self.gr_vector_to_stream_1 = gr.vector_to_stream(
gr.sizeof_gr_complex * 1, fft_size)
self.gr_vector_to_stream_0_2 = gr.vector_to_stream(
gr.sizeof_gr_complex * 1, fft_size)
self.gr_vector_to_stream_0_1 = gr.vector_to_stream(
gr.sizeof_gr_complex * 1, fft_size)
self.gr_vector_to_stream_0_0 = gr.vector_to_stream(
gr.sizeof_gr_complex * 1, fft_size)
self.gr_vector_to_stream_0 = gr.vector_to_stream(
gr.sizeof_float * 1, fft_size)
self.gr_vector_source_x_0_0_0 = gr.vector_source_c(
(gen_pss_fd(N_id_2, fft_size, False).get_data()), True, fft_size)
self.gr_vector_source_x_0_0 = gr.vector_source_c(
(gen_pss_fd(N_id_2, fft_size, False).get_data()), True, fft_size)
self.gr_vector_source_x_0 = gr.vector_source_c(
(gen_sss_fd(N_id_1, N_id_2, fft_size).get_sss(True)), True,
fft_size)
self.gr_stream_to_vector_0_0 = gr.stream_to_vector(
gr.sizeof_gr_complex * 1, fft_size)
self.gr_stream_to_vector_0 = gr.stream_to_vector(
gr.sizeof_gr_complex * 1, fft_size)
self.gr_repeat_0 = gr.repeat(gr.sizeof_float * 1, fft_size)
self.gr_null_sink_0_0 = gr.null_sink(gr.sizeof_gr_complex * 1)
self.gr_null_sink_0 = gr.null_sink(gr.sizeof_gr_complex * 1)
self.gr_noise_source_x_0 = gr.noise_source_c(gr.GR_GAUSSIAN,
noise_level, 0)
self.gr_multiply_xx_1 = gr.multiply_vcc(1)
self.gr_multiply_xx_0 = gr.multiply_vcc(fft_size)
self.gr_multiply_const_vxx_1 = gr.multiply_const_vcc((1 / 1500., ))
self.gr_multiply_const_vxx_0 = gr.multiply_const_vcc(
(exp(rot * 2 * numpy.pi * 1j), ))
self.gr_interleave_0 = gr.interleave(gr.sizeof_gr_complex * fft_size)
self.gr_integrate_xx_0 = gr.integrate_ff(fft_size)
self.gr_float_to_complex_0_0 = gr.float_to_complex(1)
self.gr_float_to_complex_0 = gr.float_to_complex(1)
self.gr_file_source_0 = gr.file_source(
gr.sizeof_gr_complex * 1,
"/home/user/git/gr-lte/gr-lte/test/foo_pss0_sss_in.cfile", True)
self.gr_fft_vxx_1 = gr.fft_vcc(fft_size, False,
(window.blackmanharris(1024)), True, 1)
self.gr_fft_vxx_0 = gr.fft_vcc(fft_size, True,
(window.blackmanharris(1024)), True, 1)
self.gr_divide_xx_0_1 = gr.divide_cc(1)
self.gr_divide_xx_0_0 = gr.divide_ff(1)
self.gr_divide_xx_0 = gr.divide_cc(1)
self.gr_deinterleave_0 = gr.deinterleave(gr.sizeof_gr_complex *
fft_size)
self.gr_conjugate_cc_1 = gr.conjugate_cc()
self.gr_conjugate_cc_0 = gr.conjugate_cc()
self.gr_complex_to_mag_squared_0_0 = gr.complex_to_mag_squared(1)
self.gr_complex_to_mag_squared_0 = gr.complex_to_mag_squared(fft_size)
self.gr_add_xx_0 = gr.add_vcc(1)
self.gr_add_const_vxx_0 = gr.add_const_vff((1, ))
self.const_source_x_0_0 = gr.sig_source_f(0, gr.GR_CONST_WAVE, 0, 0, 0)
self.const_source_x_0 = gr.sig_source_f(0, gr.GR_CONST_WAVE, 0, 0, 0)
##################################################
# Connections
##################################################
self.connect((self.gr_file_source_0, 0),
(self.gr_stream_to_vector_0, 0))
self.connect((self.gr_conjugate_cc_0, 0),
(self.gr_stream_to_vector_0_0, 0))
self.connect((self.gr_stream_to_vector_0_0, 0),
(self.gr_multiply_xx_0, 1))
self.connect((self.gr_deinterleave_0, 0), (self.gr_multiply_xx_0, 0))
self.connect((self.gr_multiply_xx_0, 0),
(self.gr_complex_to_mag_squared_0, 0))
self.connect((self.gr_complex_to_mag_squared_0, 0),
(self.gr_vector_to_stream_0, 0))
self.connect((self.gr_vector_to_stream_0, 0),
(self.gr_integrate_xx_0, 0))
self.connect((self.gr_integrate_xx_0, 0), (self.gr_repeat_0, 0))
self.connect((self.gr_multiply_xx_0, 0),
(self.gr_vector_to_stream_0_0, 0))
self.connect((self.gr_vector_to_stream_0_1, 0),
(self.gr_multiply_xx_1, 1))
self.connect((self.gr_divide_xx_0, 0), (self.gr_multiply_xx_1, 0))
self.connect((self.gr_float_to_complex_0, 0), (self.gr_divide_xx_0, 1))
self.connect((self.gr_conjugate_cc_1, 0), (self.gr_divide_xx_0, 0))
self.connect((self.gr_deinterleave_0, 1),
(self.gr_vector_to_stream_0_1, 0))
self.connect((self.gr_repeat_0, 0), (self.gr_float_to_complex_0, 0))
self.connect((self.const_source_x_0, 0),
(self.gr_float_to_complex_0, 1))
self.connect((self.gr_vector_to_stream_0_0, 0),
(self.gr_conjugate_cc_1, 0))
self.connect((self.gr_vector_to_stream_0_0, 0),
(self.gr_complex_to_mag_squared_0_0, 0))
self.connect((self.gr_complex_to_mag_squared_0_0, 0),
(self.gr_divide_xx_0_0, 0))
self.connect((self.gr_repeat_0, 0), (self.gr_divide_xx_0_0, 1))
self.connect((self.gr_divide_xx_0_0, 0), (self.gr_add_const_vxx_0, 0))
self.connect((self.gr_add_const_vxx_0, 0),
(self.gr_float_to_complex_0_0, 0))
self.connect((self.const_source_x_0_0, 0),
(self.gr_float_to_complex_0_0, 1))
self.connect((self.gr_float_to_complex_0_0, 0),
(self.gr_divide_xx_0_1, 1))
self.connect((self.gr_multiply_xx_1, 0), (self.gr_divide_xx_0_1, 0))
self.connect((self.gr_stream_to_vector_0, 0), (self.gr_fft_vxx_0, 0))
self.connect((self.gr_fft_vxx_0, 0), (self.gr_deinterleave_0, 0))
self.connect((self.gr_vector_to_stream_0_2, 0),
(self.gr_conjugate_cc_0, 0))
self.connect((self.gr_divide_xx_0_1, 0), (self.gr_null_sink_0, 0))
self.connect((self.gr_vector_source_x_0, 0), (self.gr_interleave_0, 1))
self.connect((self.gr_interleave_0, 0), (self.gr_fft_vxx_1, 0))
self.connect((self.gr_fft_vxx_1, 0), (self.gr_vector_to_stream_1, 0))
self.connect((self.gr_vector_source_x_0_0, 0),
(self.gr_interleave_0, 0))
self.connect((self.gr_vector_source_x_0_0_0, 0),
(self.gr_vector_to_stream_0_2, 0))
self.connect((self.gr_noise_source_x_0, 0), (self.gr_add_xx_0, 1))
self.connect((self.gr_vector_to_stream_1, 0), (self.gr_add_xx_0, 0))
self.connect((self.gr_add_xx_0, 0), (self.gr_multiply_const_vxx_0, 0))
self.connect((self.gr_vector_to_stream_0_1, 0),
(self.gr_multiply_const_vxx_1, 0))
self.connect((self.gr_multiply_const_vxx_0, 0),
(self.gr_null_sink_0_0, 0))
self.connect((self.gr_multiply_const_vxx_1, 0),
(self.wxgui_scopesink2_0, 1))
self.connect((self.gr_divide_xx_0_1, 0), (self.wxgui_scopesink2_0, 0))
def test_div_ff_2(self):
src1_data = (5, 9, -15, 1024)
src2_data = (10, 3, -5, 64)
expected_result = (0.5, 3, 3, 16)
op = gr.divide_ff()
self.help_ff((src1_data, src2_data), expected_result, op)
def __init__(self, subc, vlen, ss):
gr.hier_block2.__init__(
self, "new_snr_estimator",
gr.io_signature(1, 1, gr.sizeof_gr_complex * vlen),
gr.io_signature(1, 1, gr.sizeof_float))
print "Created Milan's SNR estimator"
trigger = [0] * vlen
trigger[0] = 1
u = range(vlen / ss * (ss - 1))
zeros_ind = map(lambda z: z + 1 + z / (ss - 1), u)
skip1 = skip(gr.sizeof_gr_complex, vlen)
for x in zeros_ind:
skip1.skip(x)
#print "skipped zeros",zeros_ind
v = range(vlen / ss)
ones_ind = map(lambda z: z * ss, v)
skip2 = skip(gr.sizeof_gr_complex, vlen)
for x in ones_ind:
skip2.skip(x)
#print "skipped ones",ones_ind
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, vlen)
s2v1 = gr.stream_to_vector(gr.sizeof_gr_complex, vlen / ss)
trigger_src_1 = gr.vector_source_b(trigger, True)
s2v2 = gr.stream_to_vector(gr.sizeof_gr_complex, vlen / ss * (ss - 1))
trigger_src_2 = gr.vector_source_b(trigger, True)
mag_sq_ones = gr.complex_to_mag_squared(vlen / ss)
mag_sq_zeros = gr.complex_to_mag_squared(vlen / ss * (ss - 1))
filt_ones = gr.single_pole_iir_filter_ff(0.1, vlen / ss)
filt_zeros = gr.single_pole_iir_filter_ff(0.1, vlen / ss * (ss - 1))
sum_ones = vector_sum_vff(vlen / ss)
sum_zeros = vector_sum_vff(vlen / ss * (ss - 1))
D = gr.divide_ff()
P = gr.multiply_ff()
mult1 = gr.multiply_const_ff(ss - 1.0)
add1 = gr.add_const_ff(-1.0)
mult2 = gr.multiply_const_ff(1. / ss)
scsnrdb = gr.nlog10_ff(10, 1, 0)
filt_end = gr.single_pole_iir_filter_ff(0.1)
self.connect(self, v2s, skip1, s2v1, mag_sq_ones, filt_ones, sum_ones)
self.connect(trigger_src_1, (skip1, 1))
self.connect(v2s, skip2, s2v2, mag_sq_zeros, filt_zeros, sum_zeros)
self.connect(trigger_src_2, (skip2, 1))
self.connect(sum_ones, D)
self.connect(sum_zeros, (D, 1))
self.connect(D, mult1, add1, mult2)
self.connect(mult2, scsnrdb, filt_end, self)
def __init__(self, fft_length, cp_length, logging=False):
"""
OFDM synchronization using PN Correlation:
T. M. Schmidl and D. C. Cox, "Robust Frequency and Timing
Synchonization for OFDM," IEEE Trans. Communications, vol. 45,
no. 12, 1997. Improved with averaging over the whole FFT and
peak averaging over cp_length.
"""
gr.hier_block2.__init__(self, "ofdm_sync_pn",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length/2)
self.conjg = gr.conjugate_cc();
self.corr = gr.multiply_cc();
moving_sum_taps = [1.0 for i in range(fft_length//2)]
self.moving_sum_filter = gr.fir_filter_ccf(1,moving_sum_taps)
self.inputmag2 = gr.complex_to_mag_squared()
#movingsum2_taps = [0.125 for i in range(fft_length*4)]
movingsum2_taps = [0.5 for i in range(fft_length*4)]
self.inputmovingsum = gr.fir_filter_fff(1,movingsum2_taps)
self.square = gr.multiply_ff()
self.normalize = gr.divide_ff()
self.c2mag = gr.complex_to_mag_squared()
self.angle = gr.complex_to_arg()
self.sample_and_hold = flex.sample_and_hold_ff()
self.sub1 = gr.add_const_ff(-1)
# linklab, change peak detector parameters: use higher threshold to detect rise/fall of peak
#self.pk_detect = gr.peak_detector_fb(0.20, 0.20, 30, 0.001)
self.pk_detect = flex.peak_detector_fb(0.7, 0.7, 30, 0.001) # linklab
#self.pk_detect = gr.peak_detector2_fb(9)
self.connect(self, self.input)
# Lower branch:
self.connect(self.input, self.delay)
self.connect(self.input, (self.corr,0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr,1))
self.connect(self.corr, self.moving_sum_filter)
self.connect(self.moving_sum_filter, self.c2mag)
self.connect(self.moving_sum_filter, self.angle)
self.connect(self.angle, (self.sample_and_hold,0))
self.connect(self.c2mag, (self.normalize,0))
# Upper branch
self.connect(self.input, self.inputmag2, self.inputmovingsum)
self.connect(self.inputmovingsum, (self.square,0))
self.connect(self.inputmovingsum, (self.square,1))
self.connect(self.square, (self.normalize,1))
matched_filter_taps = [1.0/cp_length for i in range(cp_length)]
self.matched_filter = gr.fir_filter_fff(1,matched_filter_taps)
self.connect(self.normalize, self.matched_filter)
# linklab, provide the signal power into peak detector, linklab
self.connect(self.square, (self.pk_detect,1))
self.connect(self.matched_filter, self.sub1, (self.pk_detect, 0))
self.connect(self.pk_detect, (self.sample_and_hold,1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self,0))
self.connect(self.pk_detect, (self,1))
if logging:
self.connect(self.square, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-square.dat"))
self.connect(self.c2mag, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-c2mag.dat"))
self.connect(self.matched_filter, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-mf_f.dat"))
self.connect(self.sub1, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-sub1.dat"))
self.connect(self.normalize, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-theta_f.dat"))
self.connect(self.angle, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-epsilon_f.dat"))
self.connect(self.pk_detect, gr.file_sink(gr.sizeof_char, "ofdm_sync_pn-peaks_b.dat"))
self.connect(self.sample_and_hold, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-sample_and_hold_f.dat"))
self.connect(self.input, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_pn-input_c.dat"))